upload unimernet_base/small/tiny
Browse files- models/MFR/unimernet_base/README.md +32 -0
- models/MFR/unimernet_base/config.json +193 -0
- models/MFR/unimernet_base/preprocessor_config.json +36 -0
- models/MFR/unimernet_base/pytorch_model.pth +3 -0
- models/MFR/unimernet_base/tokenizer.json +0 -0
- models/MFR/unimernet_base/tokenizer_config.json +205 -0
- models/MFR/unimernet_small/README.md +32 -0
- models/MFR/unimernet_small/config.json +193 -0
- models/MFR/unimernet_small/preprocessor_config.json +36 -0
- models/MFR/unimernet_small/pytorch_model.pth +3 -0
- models/MFR/unimernet_small/tokenizer.json +0 -0
- models/MFR/unimernet_small/tokenizer_config.json +205 -0
- models/MFR/unimernet_tiny/README.md +32 -0
- models/MFR/unimernet_tiny/config.json +193 -0
- models/MFR/unimernet_tiny/preprocessor_config.json +36 -0
- models/MFR/unimernet_tiny/pytorch_model.pth +3 -0
- models/MFR/unimernet_tiny/tokenizer.json +0 -0
- models/MFR/unimernet_tiny/tokenizer_config.json +205 -0
models/MFR/unimernet_base/README.md
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---
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license: apache-2.0
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---
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## UniMERNet: A Universal Network for Mathematical Expression Recognition in Real-World Scenarios.
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Visit our GitHub repository at [UniMERNet](https://github.com/opendatalab/unimernet) for more information.
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## Citations
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```
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@misc{wang2024unimernet,
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title={UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition},
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author={Bin Wang and Zhuangcheng Gu and Chao Xu and Bo Zhang and Botian Shi and Conghui He},
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year={2024},
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eprint={2404.15254},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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@misc{conghui2022opendatalab,
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author={He, Conghui and Li, Wei and Jin, Zhenjiang and Wang, Bin and Xu, Chao and Lin, Dahua},
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title={OpenDataLab: Empowering General Artificial Intelligence with Open Datasets},
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howpublished = {\url{https://opendatalab.com}},
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year={2022}
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}
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```
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## MD5 checksums
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```
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97f4867b4ff4e9a96c8daba8aaa793b4 tokenizer_config.json
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351652071425d3d36a634ccc8efb22e8 tokenizer.json
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ff4391872dad6688f21ed140009d817b pytorch_model.pth
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```
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models/MFR/unimernet_base/config.json
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{
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"_name_or_path": "unimernet/checkpoint-300000",
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"architectures": [
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"VisionEncoderDecoderModel"
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],
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"decoder": {
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"_name_or_path": "",
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"add_cross_attention": true,
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"architectures": null,
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"d_model": 1024,
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"decoder_layers": 8,
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"diversity_penalty": 0.0,
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"do_sample": false,
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"early_stopping": false,
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"encoder_attention_heads": 16,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 12,
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"encoder_no_repeat_ngram_size": 0,
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"forced_eos_token_id": 2,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1"
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},
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"init_std": 0.02,
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"is_decoder": true,
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},
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"torch_dtype": "float16",
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"transformers_version": "4.36.0"
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193 |
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}
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models/MFR/unimernet_base/preprocessor_config.json
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{
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"do_align_long_axis": false,
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"do_normalize": false,
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"do_pad": false,
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"do_rescale": false,
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"do_resize": false,
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"do_thumbnail": false,
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8 |
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"feature_extractor_type": "DonutFeatureExtractor",
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"image_mean": [
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0.485,
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],
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"image_processor_type": "VariableDonutImageProcessor",
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"image_std": [
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],
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"max_size": {
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"height": 192,
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"width": 672
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},
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"patch_size": [
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4,
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],
|
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"processor_class": "VariableDonutProcessor",
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"resample": 2,
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30 |
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"rescale_factor": 0.00392156862745098,
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31 |
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"size": [
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192,
|
33 |
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672
|
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],
|
35 |
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"train": false
|
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}
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models/MFR/unimernet_base/pytorch_model.pth
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:16cd0891233cfee3c11215a7b87306f160f7e7f3f52091a6253751c149a8c180
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size 1300760949
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models/MFR/unimernet_base/tokenizer.json
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models/MFR/unimernet_base/tokenizer_config.json
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|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"0": {
|
4 |
+
"content": "<s>",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
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"special": true
|
10 |
+
},
|
11 |
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"1": {
|
12 |
+
"content": "<pad>",
|
13 |
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|
14 |
+
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|
15 |
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"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"2": {
|
20 |
+
"content": "</s>",
|
21 |
+
"lstrip": false,
|
22 |
+
"normalized": false,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": true
|
26 |
+
},
|
27 |
+
"3": {
|
28 |
+
"content": "<unk>",
|
29 |
+
"lstrip": false,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": false,
|
32 |
+
"single_word": false,
|
33 |
+
"special": true
|
34 |
+
},
|
35 |
+
"4": {
|
36 |
+
"content": "[START_REF]",
|
37 |
+
"lstrip": false,
|
38 |
+
"normalized": false,
|
39 |
+
"rstrip": false,
|
40 |
+
"single_word": false,
|
41 |
+
"special": true
|
42 |
+
},
|
43 |
+
"5": {
|
44 |
+
"content": "[END_REF]",
|
45 |
+
"lstrip": false,
|
46 |
+
"normalized": false,
|
47 |
+
"rstrip": false,
|
48 |
+
"single_word": false,
|
49 |
+
"special": true
|
50 |
+
},
|
51 |
+
"6": {
|
52 |
+
"content": "[IMAGE]",
|
53 |
+
"lstrip": false,
|
54 |
+
"normalized": false,
|
55 |
+
"rstrip": false,
|
56 |
+
"single_word": false,
|
57 |
+
"special": true
|
58 |
+
},
|
59 |
+
"7": {
|
60 |
+
"content": "<fragments>",
|
61 |
+
"lstrip": false,
|
62 |
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"normalized": false,
|
63 |
+
"rstrip": false,
|
64 |
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"single_word": false,
|
65 |
+
"special": true
|
66 |
+
},
|
67 |
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"8": {
|
68 |
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"content": "</fragments>",
|
69 |
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"lstrip": false,
|
70 |
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"normalized": false,
|
71 |
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|
72 |
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"single_word": false,
|
73 |
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"special": true
|
74 |
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},
|
75 |
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"9": {
|
76 |
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"content": "<work>",
|
77 |
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|
78 |
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|
79 |
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|
80 |
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"single_word": false,
|
81 |
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"special": true
|
82 |
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},
|
83 |
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"10": {
|
84 |
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"content": "</work>",
|
85 |
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|
86 |
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|
87 |
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|
88 |
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"single_word": false,
|
89 |
+
"special": true
|
90 |
+
},
|
91 |
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"11": {
|
92 |
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"content": "[START_SUP]",
|
93 |
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|
94 |
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|
95 |
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|
96 |
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"single_word": false,
|
97 |
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"special": true
|
98 |
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},
|
99 |
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"12": {
|
100 |
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"content": "[END_SUP]",
|
101 |
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"lstrip": false,
|
102 |
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|
103 |
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|
104 |
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"single_word": false,
|
105 |
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"special": true
|
106 |
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},
|
107 |
+
"13": {
|
108 |
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"content": "[START_SUB]",
|
109 |
+
"lstrip": false,
|
110 |
+
"normalized": false,
|
111 |
+
"rstrip": false,
|
112 |
+
"single_word": false,
|
113 |
+
"special": true
|
114 |
+
},
|
115 |
+
"14": {
|
116 |
+
"content": "[END_SUB]",
|
117 |
+
"lstrip": false,
|
118 |
+
"normalized": false,
|
119 |
+
"rstrip": false,
|
120 |
+
"single_word": false,
|
121 |
+
"special": true
|
122 |
+
},
|
123 |
+
"15": {
|
124 |
+
"content": "[START_DNA]",
|
125 |
+
"lstrip": false,
|
126 |
+
"normalized": false,
|
127 |
+
"rstrip": false,
|
128 |
+
"single_word": false,
|
129 |
+
"special": true
|
130 |
+
},
|
131 |
+
"16": {
|
132 |
+
"content": "[END_DNA]",
|
133 |
+
"lstrip": false,
|
134 |
+
"normalized": false,
|
135 |
+
"rstrip": false,
|
136 |
+
"single_word": false,
|
137 |
+
"special": true
|
138 |
+
},
|
139 |
+
"17": {
|
140 |
+
"content": "[START_AMINO]",
|
141 |
+
"lstrip": false,
|
142 |
+
"normalized": false,
|
143 |
+
"rstrip": false,
|
144 |
+
"single_word": false,
|
145 |
+
"special": true
|
146 |
+
},
|
147 |
+
"18": {
|
148 |
+
"content": "[END_AMINO]",
|
149 |
+
"lstrip": false,
|
150 |
+
"normalized": false,
|
151 |
+
"rstrip": false,
|
152 |
+
"single_word": false,
|
153 |
+
"special": true
|
154 |
+
},
|
155 |
+
"19": {
|
156 |
+
"content": "[START_SMILES]",
|
157 |
+
"lstrip": false,
|
158 |
+
"normalized": false,
|
159 |
+
"rstrip": false,
|
160 |
+
"single_word": false,
|
161 |
+
"special": true
|
162 |
+
},
|
163 |
+
"20": {
|
164 |
+
"content": "[END_SMILES]",
|
165 |
+
"lstrip": false,
|
166 |
+
"normalized": false,
|
167 |
+
"rstrip": false,
|
168 |
+
"single_word": false,
|
169 |
+
"special": true
|
170 |
+
},
|
171 |
+
"21": {
|
172 |
+
"content": "[START_I_SMILES]",
|
173 |
+
"lstrip": false,
|
174 |
+
"normalized": false,
|
175 |
+
"rstrip": false,
|
176 |
+
"single_word": false,
|
177 |
+
"special": true
|
178 |
+
},
|
179 |
+
"22": {
|
180 |
+
"content": "[END_I_SMILES]",
|
181 |
+
"lstrip": false,
|
182 |
+
"normalized": false,
|
183 |
+
"rstrip": false,
|
184 |
+
"single_word": false,
|
185 |
+
"special": true
|
186 |
+
}
|
187 |
+
},
|
188 |
+
"additional_special_tokens": [],
|
189 |
+
"bos_token": "<s>",
|
190 |
+
"clean_up_tokenization_spaces": false,
|
191 |
+
"eos_token": "</s>",
|
192 |
+
"max_length": 4096,
|
193 |
+
"model_max_length": 768,
|
194 |
+
"pad_to_multiple_of": null,
|
195 |
+
"pad_token": "<pad>",
|
196 |
+
"pad_token_type_id": 0,
|
197 |
+
"padding_side": "right",
|
198 |
+
"processor_class": "VariableDonutProcessor",
|
199 |
+
"stride": 0,
|
200 |
+
"tokenizer_class": "NougatTokenizer",
|
201 |
+
"truncation_side": "right",
|
202 |
+
"truncation_strategy": "longest_first",
|
203 |
+
"unk_token": "<unk>",
|
204 |
+
"vocab_file": null
|
205 |
+
}
|
models/MFR/unimernet_small/README.md
ADDED
@@ -0,0 +1,32 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
---
|
4 |
+
## UniMERNet: A Universal Network for Mathematical Expression Recognition in Real-World Scenarios.
|
5 |
+
|
6 |
+
Visit our GitHub repository at [UniMERNet](https://github.com/opendatalab/unimernet) for more information.
|
7 |
+
|
8 |
+
## Citations
|
9 |
+
```
|
10 |
+
@misc{wang2024unimernet,
|
11 |
+
title={UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition},
|
12 |
+
author={Bin Wang and Zhuangcheng Gu and Chao Xu and Bo Zhang and Botian Shi and Conghui He},
|
13 |
+
year={2024},
|
14 |
+
eprint={2404.15254},
|
15 |
+
archivePrefix={arXiv},
|
16 |
+
primaryClass={cs.CV}
|
17 |
+
}
|
18 |
+
|
19 |
+
@misc{conghui2022opendatalab,
|
20 |
+
author={He, Conghui and Li, Wei and Jin, Zhenjiang and Wang, Bin and Xu, Chao and Lin, Dahua},
|
21 |
+
title={OpenDataLab: Empowering General Artificial Intelligence with Open Datasets},
|
22 |
+
howpublished = {\url{https://opendatalab.com}},
|
23 |
+
year={2022}
|
24 |
+
}
|
25 |
+
```
|
26 |
+
|
27 |
+
## MD5 checksums
|
28 |
+
```
|
29 |
+
97f4867b4ff4e9a96c8daba8aaa793b4 tokenizer_config.json
|
30 |
+
351652071425d3d36a634ccc8efb22e8 tokenizer.json
|
31 |
+
430e426354e71624fb096c5c7ad90a78 pytorch_model.pth
|
32 |
+
```
|
models/MFR/unimernet_small/config.json
ADDED
@@ -0,0 +1,193 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "unimernet/checkpoint-300000",
|
3 |
+
"architectures": [
|
4 |
+
"VisionEncoderDecoderModel"
|
5 |
+
],
|
6 |
+
"decoder": {
|
7 |
+
"_name_or_path": "",
|
8 |
+
"activation_dropout": 0.0,
|
9 |
+
"activation_function": "gelu",
|
10 |
+
"add_cross_attention": true,
|
11 |
+
"add_final_layer_norm": true,
|
12 |
+
"architectures": null,
|
13 |
+
"attention_dropout": 0.0,
|
14 |
+
"bad_words_ids": null,
|
15 |
+
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|
16 |
+
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|
17 |
+
"chunk_size_feed_forward": 0,
|
18 |
+
"classifier_dropout": 0.0,
|
19 |
+
"cross_attention_hidden_size": null,
|
20 |
+
"d_model": 768,
|
21 |
+
"decoder_attention_heads": 16,
|
22 |
+
"decoder_ffn_dim": 3072,
|
23 |
+
"decoder_layerdrop": 0.0,
|
24 |
+
"decoder_layers": 8,
|
25 |
+
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|
26 |
+
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|
27 |
+
"do_sample": false,
|
28 |
+
"dropout": 0.1,
|
29 |
+
"early_stopping": false,
|
30 |
+
"encoder_attention_heads": 16,
|
31 |
+
"encoder_ffn_dim": 3072,
|
32 |
+
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|
33 |
+
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|
34 |
+
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|
35 |
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|
36 |
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|
37 |
+
"finetuning_task": null,
|
38 |
+
"forced_bos_token_id": null,
|
39 |
+
"forced_eos_token_id": 2,
|
40 |
+
"id2label": {
|
41 |
+
"0": "LABEL_0",
|
42 |
+
"1": "LABEL_1"
|
43 |
+
},
|
44 |
+
"init_std": 0.02,
|
45 |
+
"is_decoder": true,
|
46 |
+
"is_encoder_decoder": false,
|
47 |
+
"label2id": {
|
48 |
+
"LABEL_0": 0,
|
49 |
+
"LABEL_1": 1
|
50 |
+
},
|
51 |
+
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|
52 |
+
"max_length": 20,
|
53 |
+
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|
54 |
+
"min_length": 0,
|
55 |
+
"model_type": "mbart",
|
56 |
+
"no_repeat_ngram_size": 0,
|
57 |
+
"num_beam_groups": 1,
|
58 |
+
"num_beams": 1,
|
59 |
+
"num_hidden_layers": 12,
|
60 |
+
"num_return_sequences": 1,
|
61 |
+
"output_attentions": false,
|
62 |
+
"output_hidden_states": false,
|
63 |
+
"output_scores": false,
|
64 |
+
"pad_token_id": 1,
|
65 |
+
"prefix": null,
|
66 |
+
"problem_type": null,
|
67 |
+
"pruned_heads": {},
|
68 |
+
"remove_invalid_values": false,
|
69 |
+
"repetition_penalty": 1.0,
|
70 |
+
"return_dict": true,
|
71 |
+
"return_dict_in_generate": false,
|
72 |
+
"scale_embedding": true,
|
73 |
+
"sep_token_id": null,
|
74 |
+
"suppress_tokens": null,
|
75 |
+
"task_specific_params": null,
|
76 |
+
"temperature": 1.0,
|
77 |
+
"tf_legacy_loss": false,
|
78 |
+
"tie_encoder_decoder": false,
|
79 |
+
"tie_word_embeddings": false,
|
80 |
+
"tokenizer_class": null,
|
81 |
+
"top_k": 50,
|
82 |
+
"top_p": 1.0,
|
83 |
+
"torch_dtype": null,
|
84 |
+
"torchscript": false,
|
85 |
+
"typical_p": 1.0,
|
86 |
+
"use_bfloat16": false,
|
87 |
+
"use_cache": true,
|
88 |
+
"vocab_size": 50000
|
89 |
+
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models/MFR/unimernet_small/preprocessor_config.json
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models/MFR/unimernet_small/tokenizer_config.json
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models/MFR/unimernet_tiny/README.md
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
---
|
4 |
+
## UniMERNet: A Universal Network for Mathematical Expression Recognition in Real-World Scenarios.
|
5 |
+
|
6 |
+
Visit our GitHub repository at [UniMERNet](https://github.com/opendatalab/unimernet) for more information.
|
7 |
+
|
8 |
+
## Citations
|
9 |
+
```
|
10 |
+
@misc{wang2024unimernet,
|
11 |
+
title={UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition},
|
12 |
+
author={Bin Wang and Zhuangcheng Gu and Chao Xu and Bo Zhang and Botian Shi and Conghui He},
|
13 |
+
year={2024},
|
14 |
+
eprint={2404.15254},
|
15 |
+
archivePrefix={arXiv},
|
16 |
+
primaryClass={cs.CV}
|
17 |
+
}
|
18 |
+
|
19 |
+
@misc{conghui2022opendatalab,
|
20 |
+
author={He, Conghui and Li, Wei and Jin, Zhenjiang and Wang, Bin and Xu, Chao and Lin, Dahua},
|
21 |
+
title={OpenDataLab: Empowering General Artificial Intelligence with Open Datasets},
|
22 |
+
howpublished = {\url{https://opendatalab.com}},
|
23 |
+
year={2022}
|
24 |
+
}
|
25 |
+
```
|
26 |
+
|
27 |
+
## MD5 checksums
|
28 |
+
```
|
29 |
+
97f4867b4ff4e9a96c8daba8aaa793b4 tokenizer_config.json
|
30 |
+
351652071425d3d36a634ccc8efb22e8 tokenizer.json
|
31 |
+
72b53a2152af43a57f8d5eebf8e31562 pytorch_model.pth
|
32 |
+
```
|
models/MFR/unimernet_tiny/config.json
ADDED
@@ -0,0 +1,193 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "unimernet/checkpoint-300000",
|
3 |
+
"architectures": [
|
4 |
+
"VisionEncoderDecoderModel"
|
5 |
+
],
|
6 |
+
"decoder": {
|
7 |
+
"_name_or_path": "",
|
8 |
+
"activation_dropout": 0.0,
|
9 |
+
"activation_function": "gelu",
|
10 |
+
"add_cross_attention": true,
|
11 |
+
"add_final_layer_norm": true,
|
12 |
+
"architectures": null,
|
13 |
+
"attention_dropout": 0.0,
|
14 |
+
"bad_words_ids": null,
|
15 |
+
"begin_suppress_tokens": null,
|
16 |
+
"bos_token_id": 0,
|
17 |
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|
18 |
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"classifier_dropout": 0.0,
|
19 |
+
"cross_attention_hidden_size": null,
|
20 |
+
"d_model": 512,
|
21 |
+
"decoder_attention_heads": 16,
|
22 |
+
"decoder_ffn_dim": 2048,
|
23 |
+
"decoder_layerdrop": 0.0,
|
24 |
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"decoder_layers": 8,
|
25 |
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"decoder_start_token_id": null,
|
26 |
+
"diversity_penalty": 0.0,
|
27 |
+
"do_sample": false,
|
28 |
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"dropout": 0.1,
|
29 |
+
"early_stopping": false,
|
30 |
+
"encoder_attention_heads": 16,
|
31 |
+
"encoder_ffn_dim": 2048,
|
32 |
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"encoder_layerdrop": 0.0,
|
33 |
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|
34 |
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|
35 |
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|
36 |
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|
37 |
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|
38 |
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|
39 |
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|
40 |
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"id2label": {
|
41 |
+
"0": "LABEL_0",
|
42 |
+
"1": "LABEL_1"
|
43 |
+
},
|
44 |
+
"init_std": 0.02,
|
45 |
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"is_decoder": true,
|
46 |
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|
47 |
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|
48 |
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|
49 |
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|
50 |
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},
|
51 |
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|
52 |
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|
53 |
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|
54 |
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|
55 |
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|
56 |
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|
57 |
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|
58 |
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|
59 |
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|
60 |
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|
61 |
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|
62 |
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|
63 |
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|
64 |
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|
65 |
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|
66 |
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|
67 |
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|
68 |
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|
69 |
+
"repetition_penalty": 1.0,
|
70 |
+
"return_dict": true,
|
71 |
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|
72 |
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|
73 |
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|
74 |
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|
75 |
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|
76 |
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|
77 |
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|
78 |
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|
79 |
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|
80 |
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|
81 |
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|
82 |
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|
83 |
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|
84 |
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|
85 |
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|
86 |
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|
87 |
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|
88 |
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"vocab_size": 50000
|
89 |
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},
|
90 |
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|
91 |
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|
92 |
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|
93 |
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|
94 |
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|
95 |
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|
96 |
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|
97 |
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|
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|
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|
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|
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|
102 |
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|
103 |
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|
104 |
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|
105 |
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|
106 |
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|
107 |
+
],
|
108 |
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|
109 |
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|
110 |
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|
111 |
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|
112 |
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|
113 |
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|
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|
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|
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|
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|
118 |
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|
119 |
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|
120 |
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|
121 |
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|
122 |
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|
123 |
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"0": "LABEL_0",
|
124 |
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"1": "LABEL_1"
|
125 |
+
},
|
126 |
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|
127 |
+
420,
|
128 |
+
420
|
129 |
+
],
|
130 |
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|
131 |
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|
132 |
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|
133 |
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|
134 |
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|
135 |
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|
136 |
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},
|
137 |
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"layer_norm_eps": 1e-05,
|
138 |
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|
139 |
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"max_length": 20,
|
140 |
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|
141 |
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|
142 |
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"model_type": "donut-swin",
|
143 |
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|
144 |
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|
145 |
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|
146 |
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"num_channels": 3,
|
147 |
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|
148 |
+
2,
|
149 |
+
4,
|
150 |
+
8,
|
151 |
+
16
|
152 |
+
],
|
153 |
+
"num_layers": 4,
|
154 |
+
"num_return_sequences": 1,
|
155 |
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|
156 |
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|
157 |
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|
158 |
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|
159 |
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|
160 |
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|
161 |
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|
162 |
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|
163 |
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|
164 |
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|
165 |
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|
166 |
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|
167 |
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|
168 |
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|
169 |
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|
170 |
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|
171 |
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|
172 |
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|
173 |
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|
174 |
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|
175 |
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|
176 |
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|
177 |
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|
178 |
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|
179 |
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|
180 |
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|
181 |
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|
182 |
+
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|
183 |
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|
184 |
+
"use_bfloat16": false,
|
185 |
+
"window_size": 5
|
186 |
+
},
|
187 |
+
"is_encoder_decoder": true,
|
188 |
+
"model_type": "vision-encoder-decoder",
|
189 |
+
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|
190 |
+
"tie_word_embeddings": false,
|
191 |
+
"torch_dtype": "float16",
|
192 |
+
"transformers_version": "4.36.0"
|
193 |
+
}
|
models/MFR/unimernet_tiny/preprocessor_config.json
ADDED
@@ -0,0 +1,36 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"do_align_long_axis": false,
|
3 |
+
"do_normalize": false,
|
4 |
+
"do_pad": false,
|
5 |
+
"do_rescale": false,
|
6 |
+
"do_resize": false,
|
7 |
+
"do_thumbnail": false,
|
8 |
+
"feature_extractor_type": "DonutFeatureExtractor",
|
9 |
+
"image_mean": [
|
10 |
+
0.485,
|
11 |
+
0.456,
|
12 |
+
0.406
|
13 |
+
],
|
14 |
+
"image_processor_type": "VariableDonutImageProcessor",
|
15 |
+
"image_std": [
|
16 |
+
0.229,
|
17 |
+
0.224,
|
18 |
+
0.225
|
19 |
+
],
|
20 |
+
"max_size": {
|
21 |
+
"height": 192,
|
22 |
+
"width": 672
|
23 |
+
},
|
24 |
+
"patch_size": [
|
25 |
+
4,
|
26 |
+
4
|
27 |
+
],
|
28 |
+
"processor_class": "VariableDonutProcessor",
|
29 |
+
"resample": 2,
|
30 |
+
"rescale_factor": 0.00392156862745098,
|
31 |
+
"size": [
|
32 |
+
192,
|
33 |
+
672
|
34 |
+
],
|
35 |
+
"train": false
|
36 |
+
}
|
models/MFR/unimernet_tiny/pytorch_model.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6f7608624e2d7549c7f0f05fcfbe073ae521328cf70f1d46374d96f9881d7371
|
3 |
+
size 430075701
|
models/MFR/unimernet_tiny/tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
models/MFR/unimernet_tiny/tokenizer_config.json
ADDED
@@ -0,0 +1,205 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
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|
|
|
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|
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|
|
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|
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|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
|
|
|
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|
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|
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|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
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|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
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1 |
+
{
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2 |
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"added_tokens_decoder": {
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3 |
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"0": {
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4 |
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20 |
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26 |
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27 |
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"3": {
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28 |
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"content": "<unk>",
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29 |
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34 |
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},
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35 |
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"4": {
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36 |
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"content": "[START_REF]",
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37 |
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38 |
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39 |
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40 |
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41 |
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42 |
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43 |
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"5": {
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44 |
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"content": "[END_REF]",
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45 |
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48 |
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49 |
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50 |
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},
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51 |
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"6": {
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52 |
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"content": "[IMAGE]",
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53 |
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54 |
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55 |
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56 |
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58 |
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},
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"7": {
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"content": "</fragments>",
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72 |
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74 |
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"9": {
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77 |
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79 |
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80 |
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84 |
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89 |
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90 |
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91 |
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92 |
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98 |
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"12": {
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100 |
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"content": "[END_SUP]",
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101 |
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102 |
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103 |
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104 |
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105 |
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106 |
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107 |
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"13": {
|
108 |
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"content": "[START_SUB]",
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109 |
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110 |
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111 |
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112 |
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113 |
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114 |
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115 |
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"14": {
|
116 |
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"content": "[END_SUB]",
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117 |
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118 |
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119 |
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120 |
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121 |
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122 |
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123 |
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"15": {
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124 |
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"content": "[START_DNA]",
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125 |
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126 |
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127 |
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128 |
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129 |
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130 |
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131 |
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132 |
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"content": "[END_DNA]",
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133 |
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134 |
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135 |
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136 |
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137 |
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138 |
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139 |
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"17": {
|
140 |
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"content": "[START_AMINO]",
|
141 |
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142 |
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143 |
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144 |
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145 |
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146 |
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147 |
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"18": {
|
148 |
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"content": "[END_AMINO]",
|
149 |
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150 |
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151 |
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152 |
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153 |
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154 |
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155 |
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156 |
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157 |
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158 |
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159 |
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160 |
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161 |
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162 |
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163 |
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164 |
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165 |
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166 |
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167 |
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168 |
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169 |
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170 |
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171 |
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172 |
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173 |
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174 |
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175 |
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176 |
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177 |
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178 |
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179 |
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180 |
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181 |
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182 |
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183 |
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184 |
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185 |
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186 |
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}
|
187 |
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},
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188 |
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|
189 |
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"bos_token": "<s>",
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190 |
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191 |
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192 |
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193 |
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194 |
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195 |
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196 |
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197 |
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198 |
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|
199 |
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|
200 |
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"tokenizer_class": "NougatTokenizer",
|
201 |
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|
202 |
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|
203 |
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"unk_token": "<unk>",
|
204 |
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|
205 |
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}
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