openvino-ci
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Browse files- README.md +66 -0
- added_tokens.json +40 -0
- config.json +42 -0
- generation_config.json +6 -0
- merges.txt +0 -0
- openvino_detokenizer.bin +3 -0
- openvino_detokenizer.xml +162 -0
- openvino_model.bin +3 -0
- openvino_model.xml +0 -0
- openvino_tokenizer.bin +3 -0
- openvino_tokenizer.xml +680 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer_config.json +324 -0
- vocab.json +0 -0
README.md
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---
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license: bsd-3-clause
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license_link: https://choosealicense.com/licenses/bsd-3-clause/
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---
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# codegen-2B-multi-int8-ov
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* Model creator: [Salesforce](https://huggingface.co/Salesforce)
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* Original model: [codegen-2B-multi](https://huggingface.co/Salesforce/codegen-2B-multi)
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## Description
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This is [codegen-2B-multi](https://huggingface.co/Salesforce/codegen-2B-multi) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf).
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## Quantization Parameters
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Weight compression was performed using `nncf.compress_weights` with the following parameters:
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* mode: **int8_asym**
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* ratio: **1**
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For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html).
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## Compatibility
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The provided OpenVINO™ IR model is compatible with:
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* OpenVINO version 2024.4.0 and higher
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* Optimum Intel 1.20.0 and higher
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## Running Model Inference
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1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
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```
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pip install optimum[openvino]
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```
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2. Run model inference:
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```
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from transformers import AutoTokenizer
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from optimum.intel.openvino import OVModelForCausalLM
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model_id = "OpenVINO/codegen-2B-multi-int8-ov"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = OVModelForCausalLM.from_pretrained(model_id)
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inputs = tokenizer("What is OpenVINO?", return_tensors="pt")
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outputs = model.generate(**inputs, max_length=200)
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text = tokenizer.batch_decode(outputs)[0]
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print(text)
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```
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For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html).
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## Limitations
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Check the original model card for [original model card](https://huggingface.co/Salesforce/codegen-2B-multi) for limitations.
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## Legal information
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The original model is distributed under [bsd-3-clause](https://choosealicense.com/licenses/bsd-3-clause/) license. More details can be found in [original model card](https://huggingface.co/Salesforce/codegen-2B-multi).
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## Disclaimer
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Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See [Intel’s Global Human Rights Principles](https://www.intel.com/content/dam/www/central-libraries/us/en/documents/policy-human-rights.pdf). Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights.
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added_tokens.json
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{
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"\t\t": 50294,
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"\t\t\t": 50293,
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"\t\t\t\t": 50292,
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"\t\t\t\t\t": 50291,
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"\t\t\t\t\t\t": 50290,
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"\t\t\t\t\t\t\t": 50289,
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"\t\t\t\t\t\t\t\t": 50288,
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"\t\t\t\t\t\t\t\t\t": 50287,
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" ": 50286,
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" ": 50284,
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" ": 50259,
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" ": 50258,
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" ": 50257
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}
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config.json
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{
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"_name_or_path": "Salesforce/codegen-2B-multi",
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"activation_function": "gelu_new",
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"architectures": [
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"CodeGenForCausalLM"
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],
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"attn_pdrop": 0.0,
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"bos_token_id": 1,
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"embd_pdrop": 0.0,
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"eos_token_id": 50256,
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"gradient_checkpointing": false,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "codegen",
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"n_ctx": 2048,
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"n_embd": 2560,
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"n_head": 32,
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"n_inner": null,
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"n_layer": 32,
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"n_positions": 2048,
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"resid_pdrop": 0.0,
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"rotary_dim": 64,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"task_specific_params": {
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"text-generation": {
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"do_sample": true,
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"max_length": 50,
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"temperature": 1.0
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}
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},
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"tie_word_embeddings": false,
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"tokenizer_class": "GPT2Tokenizer",
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"torch_dtype": "float16",
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"transformers_version": "4.45.2",
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"use_cache": true,
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"vocab_size": 51200
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 50256,
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"transformers_version": "4.45.2"
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}
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merges.txt
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The diff for this file is too large to render.
See raw diff
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openvino_detokenizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:e4268d1a0870145ef1b7ec4d701e6de4cdab7ec228618a4d686036282d56e752
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size 522554
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openvino_detokenizer.xml
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<?xml version="1.0"?>
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<net name="detokenizer" version="11">
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<layers>
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<layer id="0" name="Parameter_104645" type="Parameter" version="opset1">
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<data shape="?,?" element_type="i64" />
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<output>
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<port id="0" precision="I64" names="Parameter_104645">
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<dim>-1</dim>
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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<layer id="1" name="Convert_104656" type="Convert" version="opset1">
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<data destination_type="i32" />
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<input>
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<port id="0" precision="I64">
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<dim>-1</dim>
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<dim>-1</dim>
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</port>
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</input>
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<output>
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<port id="1" precision="I32">
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<dim>-1</dim>
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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<layer id="2" name="Constant_104620" type="Const" version="opset1">
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<data element_type="u8" shape="522554" offset="0" size="522554" />
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<output>
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<port id="0" precision="U8">
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<dim>522554</dim>
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</port>
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</output>
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</layer>
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<layer id="3" name="StringTensorUnpack_104621" type="StringTensorUnpack" version="extension">
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<data mode="begins_ends" />
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<input>
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<port id="0" precision="U8">
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<dim>522554</dim>
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</port>
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</input>
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<output>
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<port id="1" precision="I32">
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<dim>-1</dim>
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</port>
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+
<port id="2" precision="I32">
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+
<dim>-1</dim>
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+
</port>
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+
<port id="3" precision="U8">
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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<layer id="4" name="VocabDecoder_104646" type="VocabDecoder" version="extension">
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<data skip_tokens="50256" />
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<input>
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<port id="0" precision="I32">
|
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<dim>-1</dim>
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+
<dim>-1</dim>
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</port>
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+
<port id="1" precision="I32">
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+
<dim>-1</dim>
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</port>
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+
<port id="2" precision="I32">
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+
<dim>-1</dim>
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</port>
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<port id="3" precision="U8">
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<dim>-1</dim>
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</port>
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</input>
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<output>
|
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+
<port id="4" precision="I32">
|
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+
<dim>-1</dim>
|
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+
</port>
|
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+
<port id="5" precision="I32">
|
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+
<dim>-1</dim>
|
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+
</port>
|
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+
<port id="6" precision="I32">
|
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+
<dim>-1</dim>
|
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+
</port>
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+
<port id="7" precision="I32">
|
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<dim>-1</dim>
|
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</port>
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<port id="8" precision="U8">
|
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<dim>-1</dim>
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</port>
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</output>
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</layer>
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<layer id="5" name="FuzeRagged_104647" type="FuzeRagged" version="extension">
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<input>
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<port id="0" precision="I32">
|
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<dim>-1</dim>
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</port>
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+
<port id="1" precision="I32">
|
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<dim>-1</dim>
|
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</port>
|
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<port id="2" precision="I32">
|
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<dim>-1</dim>
|
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</port>
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<port id="3" precision="I32">
|
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<dim>-1</dim>
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</port>
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</input>
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<output>
|
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<port id="4" precision="I32">
|
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+
<dim>-1</dim>
|
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</port>
|
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+
<port id="5" precision="I32">
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<dim>-1</dim>
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</port>
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</output>
|
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</layer>
|
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<layer id="6" name="StringTensorPack_104648" type="StringTensorPack" version="extension">
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<data mode="begins_ends" />
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<input>
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<port id="0" precision="I32">
|
118 |
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<dim>-1</dim>
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</port>
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<port id="1" precision="I32">
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<dim>-1</dim>
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</port>
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<port id="2" precision="U8">
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<dim>-1</dim>
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</port>
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</input>
|
127 |
+
<output>
|
128 |
+
<port id="3" precision="STRING" names="string_output">
|
129 |
+
<dim>-1</dim>
|
130 |
+
</port>
|
131 |
+
</output>
|
132 |
+
</layer>
|
133 |
+
<layer id="7" name="Result_104649" type="Result" version="opset1">
|
134 |
+
<input>
|
135 |
+
<port id="0" precision="STRING">
|
136 |
+
<dim>-1</dim>
|
137 |
+
</port>
|
138 |
+
</input>
|
139 |
+
</layer>
|
140 |
+
</layers>
|
141 |
+
<edges>
|
142 |
+
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|
143 |
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|
144 |
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146 |
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147 |
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|
149 |
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|
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|
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|
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|
155 |
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<edge from-layer="6" from-port="3" to-layer="7" to-port="0" />
|
156 |
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</edges>
|
157 |
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<rt_info>
|
158 |
+
<bos_token_id value="50256" />
|
159 |
+
<eos_token_id value="50256" />
|
160 |
+
<original_tokenizer_class value="<class 'transformers.models.codegen.tokenization_codegen_fast.CodeGenTokenizerFast'>" />
|
161 |
+
</rt_info>
|
162 |
+
</net>
|
openvino_model.bin
ADDED
@@ -0,0 +1,3 @@
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|
1 |
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version https://git-lfs.github.com/spec/v1
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|
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size 2782980472
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openvino_model.xml
ADDED
The diff for this file is too large to render.
See raw diff
|
|
openvino_tokenizer.bin
ADDED
@@ -0,0 +1,3 @@
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|
|
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|
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|
1 |
+
version https://git-lfs.github.com/spec/v1
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|
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size 1245299
|
openvino_tokenizer.xml
ADDED
@@ -0,0 +1,680 @@
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|
1 |
+
<?xml version="1.0"?>
|
2 |
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|
3 |
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|
4 |
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|
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|
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|
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|
15 |
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|
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17 |
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|
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|
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|
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|
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|
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|
544 |
+
<data destination_type="i32" />
|
545 |
+
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|
546 |
+
<port id="0" precision="BOOL">
|
547 |
+
<dim>-1</dim>
|
548 |
+
<dim>-1</dim>
|
549 |
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|
550 |
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|
551 |
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|
552 |
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|
553 |
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<dim>-1</dim>
|
554 |
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<dim>-1</dim>
|
555 |
+
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|
556 |
+
</output>
|
557 |
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</layer>
|
558 |
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<layer id="38" name="Convert_104642" type="Convert" version="opset1">
|
559 |
+
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|
560 |
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|
561 |
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|
562 |
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|
563 |
+
<dim>-1</dim>
|
564 |
+
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|
565 |
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|
566 |
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|
567 |
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<port id="1" precision="I64" names="attention_mask">
|
568 |
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<dim>-1</dim>
|
569 |
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<dim>-1</dim>
|
570 |
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|
571 |
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|
572 |
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|
573 |
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|
574 |
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|
575 |
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576 |
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|
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|
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|
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|
587 |
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|
588 |
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589 |
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|
590 |
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|
592 |
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|
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596 |
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597 |
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598 |
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599 |
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|
600 |
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627 |
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|
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670 |
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|
673 |
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<edge from-layer="40" from-port="1" to-layer="41" to-port="0" />
|
674 |
+
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|
675 |
+
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|
676 |
+
<bos_token_id value="50256" />
|
677 |
+
<eos_token_id value="50256" />
|
678 |
+
<original_tokenizer_class value="<class 'transformers.models.codegen.tokenization_codegen_fast.CodeGenTokenizerFast'>" />
|
679 |
+
</rt_info>
|
680 |
+
</net>
|
special_tokens_map.json
ADDED
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"bos_token": {
|
3 |
+
"content": "<|endoftext|>",
|
4 |
+
"lstrip": false,
|
5 |
+
"normalized": false,
|
6 |
+
"rstrip": false,
|
7 |
+
"single_word": false
|
8 |
+
},
|
9 |
+
"eos_token": {
|
10 |
+
"content": "<|endoftext|>",
|
11 |
+
"lstrip": false,
|
12 |
+
"normalized": false,
|
13 |
+
"rstrip": false,
|
14 |
+
"single_word": false
|
15 |
+
},
|
16 |
+
"unk_token": {
|
17 |
+
"content": "<|endoftext|>",
|
18 |
+
"lstrip": false,
|
19 |
+
"normalized": false,
|
20 |
+
"rstrip": false,
|
21 |
+
"single_word": false
|
22 |
+
}
|
23 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,324 @@
|
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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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|
3 |
+
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|
4 |
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|
5 |
+
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|
6 |
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|
7 |
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|
8 |
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|
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|
10 |
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|
11 |
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|
12 |
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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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|
24 |
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|
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|
26 |
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|
27 |
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|
28 |
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|
29 |
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|
30 |
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|
31 |
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|
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 |
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|
38 |
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|
39 |
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|
40 |
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|
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|
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|
43 |
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|
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|
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|
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|
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|
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|
50 |
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|
51 |
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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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|
60 |
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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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|
67 |
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68 |
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|
69 |
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|
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|
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|
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|
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|
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|
75 |
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|
76 |
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|
77 |
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|
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|
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|
80 |
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|
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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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|
89 |
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|
90 |
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|
91 |
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|
92 |
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|
93 |
+
"content": " ",
|
94 |
+
"lstrip": false,
|
95 |
+
"normalized": true,
|
96 |
+
"rstrip": false,
|
97 |
+
"single_word": false,
|
98 |
+
"special": false
|
99 |
+
},
|
100 |
+
"50268": {
|
101 |
+
"content": " ",
|
102 |
+
"lstrip": false,
|
103 |
+
"normalized": true,
|
104 |
+
"rstrip": false,
|
105 |
+
"single_word": false,
|
106 |
+
"special": false
|
107 |
+
},
|
108 |
+
"50269": {
|
109 |
+
"content": " ",
|
110 |
+
"lstrip": false,
|
111 |
+
"normalized": true,
|
112 |
+
"rstrip": false,
|
113 |
+
"single_word": false,
|
114 |
+
"special": false
|
115 |
+
},
|
116 |
+
"50270": {
|
117 |
+
"content": " ",
|
118 |
+
"lstrip": false,
|
119 |
+
"normalized": true,
|
120 |
+
"rstrip": false,
|
121 |
+
"single_word": false,
|
122 |
+
"special": false
|
123 |
+
},
|
124 |
+
"50271": {
|
125 |
+
"content": " ",
|
126 |
+
"lstrip": false,
|
127 |
+
"normalized": true,
|
128 |
+
"rstrip": false,
|
129 |
+
"single_word": false,
|
130 |
+
"special": false
|
131 |
+
},
|
132 |
+
"50272": {
|
133 |
+
"content": " ",
|
134 |
+
"lstrip": false,
|
135 |
+
"normalized": true,
|
136 |
+
"rstrip": false,
|
137 |
+
"single_word": false,
|
138 |
+
"special": false
|
139 |
+
},
|
140 |
+
"50273": {
|
141 |
+
"content": " ",
|
142 |
+
"lstrip": false,
|
143 |
+
"normalized": true,
|
144 |
+
"rstrip": false,
|
145 |
+
"single_word": false,
|
146 |
+
"special": false
|
147 |
+
},
|
148 |
+
"50274": {
|
149 |
+
"content": " ",
|
150 |
+
"lstrip": false,
|
151 |
+
"normalized": true,
|
152 |
+
"rstrip": false,
|
153 |
+
"single_word": false,
|
154 |
+
"special": false
|
155 |
+
},
|
156 |
+
"50275": {
|
157 |
+
"content": " ",
|
158 |
+
"lstrip": false,
|
159 |
+
"normalized": true,
|
160 |
+
"rstrip": false,
|
161 |
+
"single_word": false,
|
162 |
+
"special": false
|
163 |
+
},
|
164 |
+
"50276": {
|
165 |
+
"content": " ",
|
166 |
+
"lstrip": false,
|
167 |
+
"normalized": true,
|
168 |
+
"rstrip": false,
|
169 |
+
"single_word": false,
|
170 |
+
"special": false
|
171 |
+
},
|
172 |
+
"50277": {
|
173 |
+
"content": " ",
|
174 |
+
"lstrip": false,
|
175 |
+
"normalized": true,
|
176 |
+
"rstrip": false,
|
177 |
+
"single_word": false,
|
178 |
+
"special": false
|
179 |
+
},
|
180 |
+
"50278": {
|
181 |
+
"content": " ",
|
182 |
+
"lstrip": false,
|
183 |
+
"normalized": true,
|
184 |
+
"rstrip": false,
|
185 |
+
"single_word": false,
|
186 |
+
"special": false
|
187 |
+
},
|
188 |
+
"50279": {
|
189 |
+
"content": " ",
|
190 |
+
"lstrip": false,
|
191 |
+
"normalized": true,
|
192 |
+
"rstrip": false,
|
193 |
+
"single_word": false,
|
194 |
+
"special": false
|
195 |
+
},
|
196 |
+
"50280": {
|
197 |
+
"content": " ",
|
198 |
+
"lstrip": false,
|
199 |
+
"normalized": true,
|
200 |
+
"rstrip": false,
|
201 |
+
"single_word": false,
|
202 |
+
"special": false
|
203 |
+
},
|
204 |
+
"50281": {
|
205 |
+
"content": " ",
|
206 |
+
"lstrip": false,
|
207 |
+
"normalized": true,
|
208 |
+
"rstrip": false,
|
209 |
+
"single_word": false,
|
210 |
+
"special": false
|
211 |
+
},
|
212 |
+
"50282": {
|
213 |
+
"content": " ",
|
214 |
+
"lstrip": false,
|
215 |
+
"normalized": true,
|
216 |
+
"rstrip": false,
|
217 |
+
"single_word": false,
|
218 |
+
"special": false
|
219 |
+
},
|
220 |
+
"50283": {
|
221 |
+
"content": " ",
|
222 |
+
"lstrip": false,
|
223 |
+
"normalized": true,
|
224 |
+
"rstrip": false,
|
225 |
+
"single_word": false,
|
226 |
+
"special": false
|
227 |
+
},
|
228 |
+
"50284": {
|
229 |
+
"content": " ",
|
230 |
+
"lstrip": false,
|
231 |
+
"normalized": true,
|
232 |
+
"rstrip": false,
|
233 |
+
"single_word": false,
|
234 |
+
"special": false
|
235 |
+
},
|
236 |
+
"50285": {
|
237 |
+
"content": " ",
|
238 |
+
"lstrip": false,
|
239 |
+
"normalized": true,
|
240 |
+
"rstrip": false,
|
241 |
+
"single_word": false,
|
242 |
+
"special": false
|
243 |
+
},
|
244 |
+
"50286": {
|
245 |
+
"content": " ",
|
246 |
+
"lstrip": false,
|
247 |
+
"normalized": true,
|
248 |
+
"rstrip": false,
|
249 |
+
"single_word": false,
|
250 |
+
"special": false
|
251 |
+
},
|
252 |
+
"50287": {
|
253 |
+
"content": "\t\t\t\t\t\t\t\t\t",
|
254 |
+
"lstrip": false,
|
255 |
+
"normalized": true,
|
256 |
+
"rstrip": false,
|
257 |
+
"single_word": false,
|
258 |
+
"special": false
|
259 |
+
},
|
260 |
+
"50288": {
|
261 |
+
"content": "\t\t\t\t\t\t\t\t",
|
262 |
+
"lstrip": false,
|
263 |
+
"normalized": true,
|
264 |
+
"rstrip": false,
|
265 |
+
"single_word": false,
|
266 |
+
"special": false
|
267 |
+
},
|
268 |
+
"50289": {
|
269 |
+
"content": "\t\t\t\t\t\t\t",
|
270 |
+
"lstrip": false,
|
271 |
+
"normalized": true,
|
272 |
+
"rstrip": false,
|
273 |
+
"single_word": false,
|
274 |
+
"special": false
|
275 |
+
},
|
276 |
+
"50290": {
|
277 |
+
"content": "\t\t\t\t\t\t",
|
278 |
+
"lstrip": false,
|
279 |
+
"normalized": true,
|
280 |
+
"rstrip": false,
|
281 |
+
"single_word": false,
|
282 |
+
"special": false
|
283 |
+
},
|
284 |
+
"50291": {
|
285 |
+
"content": "\t\t\t\t\t",
|
286 |
+
"lstrip": false,
|
287 |
+
"normalized": true,
|
288 |
+
"rstrip": false,
|
289 |
+
"single_word": false,
|
290 |
+
"special": false
|
291 |
+
},
|
292 |
+
"50292": {
|
293 |
+
"content": "\t\t\t\t",
|
294 |
+
"lstrip": false,
|
295 |
+
"normalized": true,
|
296 |
+
"rstrip": false,
|
297 |
+
"single_word": false,
|
298 |
+
"special": false
|
299 |
+
},
|
300 |
+
"50293": {
|
301 |
+
"content": "\t\t\t",
|
302 |
+
"lstrip": false,
|
303 |
+
"normalized": true,
|
304 |
+
"rstrip": false,
|
305 |
+
"single_word": false,
|
306 |
+
"special": false
|
307 |
+
},
|
308 |
+
"50294": {
|
309 |
+
"content": "\t\t",
|
310 |
+
"lstrip": false,
|
311 |
+
"normalized": true,
|
312 |
+
"rstrip": false,
|
313 |
+
"single_word": false,
|
314 |
+
"special": false
|
315 |
+
}
|
316 |
+
},
|
317 |
+
"bos_token": "<|endoftext|>",
|
318 |
+
"clean_up_tokenization_spaces": false,
|
319 |
+
"eos_token": "<|endoftext|>",
|
320 |
+
"model_max_length": 2048,
|
321 |
+
"return_token_type_ids": false,
|
322 |
+
"tokenizer_class": "CodeGenTokenizer",
|
323 |
+
"unk_token": "<|endoftext|>"
|
324 |
+
}
|
vocab.json
ADDED
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|
|