Upload tokenizer
Browse files- README.md +199 -0
- special_tokens_map.json +8 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1001 -0
README.md
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---
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library_name: transformers
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tags: []
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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special_tokens_map.json
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@@ -0,0 +1,8 @@
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{
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"bos_token": "<|bos|>",
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"eos_token": "<|eos|>",
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"mask_token": "<|mask|>",
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"pad_token": "<|pad|>",
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"sep_token": "<|sep|>",
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"unk_token": "<|unk|>"
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}
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tokenizer.json
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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
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1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"0": {
|
4 |
+
"content": "<|bos|>",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
+
},
|
11 |
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"1": {
|
12 |
+
"content": "<|eos|>",
|
13 |
+
"lstrip": false,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
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"single_word": false,
|
17 |
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"special": true
|
18 |
+
},
|
19 |
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"2": {
|
20 |
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"content": "<|pad|>",
|
21 |
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"lstrip": false,
|
22 |
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"normalized": false,
|
23 |
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"rstrip": false,
|
24 |
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"single_word": false,
|
25 |
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"special": true
|
26 |
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},
|
27 |
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"3": {
|
28 |
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"content": "<|unk|>",
|
29 |
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"lstrip": false,
|
30 |
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"normalized": false,
|
31 |
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"rstrip": false,
|
32 |
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"single_word": false,
|
33 |
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"special": true
|
34 |
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},
|
35 |
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"4": {
|
36 |
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"content": "<|sep|>",
|
37 |
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"lstrip": false,
|
38 |
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"normalized": false,
|
39 |
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"rstrip": false,
|
40 |
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"single_word": false,
|
41 |
+
"special": true
|
42 |
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},
|
43 |
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"5": {
|
44 |
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"content": "<|mask|>",
|
45 |
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"lstrip": false,
|
46 |
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"normalized": false,
|
47 |
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"rstrip": false,
|
48 |
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"single_word": false,
|
49 |
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"special": true
|
50 |
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},
|
51 |
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"6": {
|
52 |
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"content": "<rating>",
|
53 |
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"lstrip": false,
|
54 |
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|
55 |
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"rstrip": false,
|
56 |
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|
57 |
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"special": true
|
58 |
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},
|
59 |
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"7": {
|
60 |
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"content": "</rating>",
|
61 |
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"lstrip": false,
|
62 |
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"normalized": false,
|
63 |
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"rstrip": false,
|
64 |
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|
65 |
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"special": true
|
66 |
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},
|
67 |
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"8": {
|
68 |
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"content": "<general>",
|
69 |
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"lstrip": false,
|
70 |
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"normalized": false,
|
71 |
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"rstrip": false,
|
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": "</general>",
|
77 |
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|
78 |
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|
79 |
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"rstrip": false,
|
80 |
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|
81 |
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"special": true
|
82 |
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},
|
83 |
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"10": {
|
84 |
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"content": "<character>",
|
85 |
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"lstrip": false,
|
86 |
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"normalized": false,
|
87 |
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"rstrip": false,
|
88 |
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|
89 |
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"special": true
|
90 |
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},
|
91 |
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"11": {
|
92 |
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"content": "</character>",
|
93 |
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"lstrip": false,
|
94 |
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|
95 |
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"rstrip": false,
|
96 |
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|
97 |
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"special": true
|
98 |
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},
|
99 |
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"12": {
|
100 |
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"content": "<copyright>",
|
101 |
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"lstrip": false,
|
102 |
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"normalized": false,
|
103 |
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"rstrip": false,
|
104 |
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"single_word": false,
|
105 |
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"special": true
|
106 |
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},
|
107 |
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"13": {
|
108 |
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"content": "</copyright>",
|
109 |
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"lstrip": false,
|
110 |
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"normalized": false,
|
111 |
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"rstrip": false,
|
112 |
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"single_word": false,
|
113 |
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"special": true
|
114 |
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},
|
115 |
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"14": {
|
116 |
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"content": "<|rating:sfw|>",
|
117 |
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"lstrip": false,
|
118 |
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"normalized": false,
|
119 |
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"rstrip": false,
|
120 |
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|
121 |
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"special": true
|
122 |
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},
|
123 |
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"15": {
|
124 |
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"content": "<|rating:nsfw|>",
|
125 |
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"lstrip": false,
|
126 |
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"normalized": false,
|
127 |
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"rstrip": false,
|
128 |
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"single_word": false,
|
129 |
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"special": true
|
130 |
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},
|
131 |
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"16": {
|
132 |
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"content": "<|rating:general|>",
|
133 |
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|
134 |
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"normalized": false,
|
135 |
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"rstrip": false,
|
136 |
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"single_word": false,
|
137 |
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"special": true
|
138 |
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},
|
139 |
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"17": {
|
140 |
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"content": "<|rating:sensitive|>",
|
141 |
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|
142 |
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|
143 |
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"rstrip": false,
|
144 |
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"single_word": false,
|
145 |
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"special": true
|
146 |
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},
|
147 |
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"18": {
|
148 |
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"content": "<|rating:questionable|>",
|
149 |
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"lstrip": false,
|
150 |
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"normalized": false,
|
151 |
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"rstrip": false,
|
152 |
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"single_word": false,
|
153 |
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"special": true
|
154 |
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},
|
155 |
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"19": {
|
156 |
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"content": "<|rating:explicit|>",
|
157 |
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"lstrip": false,
|
158 |
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"normalized": false,
|
159 |
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"rstrip": false,
|
160 |
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|
161 |
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"special": true
|
162 |
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},
|
163 |
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"20": {
|
164 |
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"content": "<|quality:best|>",
|
165 |
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"lstrip": false,
|
166 |
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"normalized": false,
|
167 |
+
"rstrip": false,
|
168 |
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"single_word": false,
|
169 |
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"special": true
|
170 |
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},
|
171 |
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"21": {
|
172 |
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"content": "<|quality:high|>",
|
173 |
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"lstrip": false,
|
174 |
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"normalized": false,
|
175 |
+
"rstrip": false,
|
176 |
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"single_word": false,
|
177 |
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"special": true
|
178 |
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},
|
179 |
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"22": {
|
180 |
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"content": "<|quality:normal|>",
|
181 |
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"lstrip": false,
|
182 |
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"normalized": false,
|
183 |
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|
184 |
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|
185 |
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"special": true
|
186 |
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},
|
187 |
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"23": {
|
188 |
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"content": "<|quality:low|>",
|
189 |
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|
190 |
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|
191 |
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"rstrip": false,
|
192 |
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|
193 |
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"special": true
|
194 |
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},
|
195 |
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"24": {
|
196 |
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"content": "<|quality:worst|>",
|
197 |
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"lstrip": false,
|
198 |
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"normalized": false,
|
199 |
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"rstrip": false,
|
200 |
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|
201 |
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"special": true
|
202 |
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},
|
203 |
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"25": {
|
204 |
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"content": "<|length:very_short|>",
|
205 |
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"lstrip": false,
|
206 |
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|
207 |
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"rstrip": false,
|
208 |
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|
209 |
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"special": true
|
210 |
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},
|
211 |
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"26": {
|
212 |
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"content": "<|length:short|>",
|
213 |
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|
214 |
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|
215 |
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|
216 |
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|
217 |
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"special": true
|
218 |
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},
|
219 |
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"27": {
|
220 |
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"content": "<|length:medium|>",
|
221 |
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|
222 |
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|
223 |
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|
224 |
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|
225 |
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|
226 |
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},
|
227 |
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"28": {
|
228 |
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"content": "<|length:long|>",
|
229 |
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|
230 |
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|
231 |
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|
232 |
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|
233 |
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|
234 |
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|
235 |
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"29": {
|
236 |
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"content": "<|length:very_long|>",
|
237 |
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|
238 |
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|
239 |
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|
240 |
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|
241 |
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"special": true
|
242 |
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},
|
243 |
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"30": {
|
244 |
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"content": "<|aspect_ratio:ultra_wide|>",
|
245 |
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|
246 |
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|
247 |
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|
248 |
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|
249 |
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|
250 |
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|
251 |
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"31": {
|
252 |
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253 |
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|
254 |
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|
255 |
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|
256 |
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|
257 |
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258 |
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|
259 |
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"32": {
|
260 |
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261 |
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262 |
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263 |
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264 |
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265 |
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266 |
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267 |
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"33": {
|
268 |
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"content": "<|aspect_ratio:tall|>",
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269 |
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|
270 |
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|
271 |
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272 |
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|
273 |
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274 |
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275 |
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|
276 |
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277 |
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278 |
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279 |
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|
280 |
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281 |
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282 |
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283 |
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"35": {
|
284 |
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"content": "<|input_start|>",
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285 |
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286 |
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|
287 |
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|
288 |
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|
289 |
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290 |
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291 |
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"36": {
|
292 |
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293 |
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294 |
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295 |
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296 |
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297 |
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298 |
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299 |
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"37": {
|
300 |
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301 |
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302 |
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303 |
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304 |
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305 |
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306 |
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307 |
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"38": {
|
308 |
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309 |
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310 |
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311 |
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312 |
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313 |
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