openvino-ci
commited on
Commit
•
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Parent(s):
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Upload folder using huggingface_hub
Browse files- README.md +68 -0
- config.json +29 -0
- generation_config.json +7 -0
- openvino_detokenizer.bin +3 -0
- openvino_detokenizer.xml +97 -0
- openvino_model.bin +3 -0
- openvino_model.xml +0 -0
- openvino_tokenizer.bin +3 -0
- openvino_tokenizer.xml +231 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +42 -0
README.md
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---
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license: apache-2.0
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license_link: https://choosealicense.com/licenses/apache-2.0/
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---
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# open_llama_3b_v2-int4-ov
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* Model creator: [Openlm-research](https://huggingface.co/openlm-research)
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* Original model: [open_llama_3b_v2](https://huggingface.co/openlm-research/open_llama_3b_v2)
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## Description
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This is [open_llama_3b_v2](https://huggingface.co/openlm-research/open_llama_3b_v2) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT4 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: **int4_sym**
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* ratio: **1.0**
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* group_size: **64**
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* all_layers: **True**
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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 2024.1.0 and higher
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* Optimum Intel 1.16.0 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/open_llama_3b_v2-int4-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/openlm-research/open_llama_3b_v2) for limitations.
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## Legal information
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The original model is distributed under [apache-2.0](https://choosealicense.com/licenses/apache-2.0/) license. More details can be found in [original model card](https://huggingface.co/openlm-research/open_llama_3b_v2).
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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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config.json
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{
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"_name_or_path": "openlm-research/open_llama_3b_v2",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 3200,
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"initializer_range": 0.02,
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"intermediate_size": 8640,
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"max_position_embeddings": 2048,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 26,
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"num_key_value_heads": 32,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"transformers_version": "4.42.4",
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"use_cache": true,
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"vocab_size": 32000
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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": 2,
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"pad_token_id": 0,
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"transformers_version": "4.42.4"
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}
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openvino_detokenizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:9200b58939b5f15eda267b46cd367416c6ffec891653b50930b2cb0944c0f112
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size 511574
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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_143668" 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_143668">
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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="Constant_143648" type="Const" version="opset1">
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<data element_type="u8" shape="511574" offset="0" size="511574" />
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<output>
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<port id="0" precision="U8">
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<dim>511574</dim>
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</port>
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</output>
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</layer>
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<layer id="2" name="Convert_143678" 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="3" name="SentencepieceDetokenizer_143669" type="SentencepieceDetokenizer" version="extension">
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<input>
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<port id="0" precision="U8">
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<dim>511574</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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<dim>-1</dim>
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</port>
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</input>
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<output>
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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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<port id="4" 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="StringTensorPack_143670" 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">
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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>
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<output>
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<port id="3" precision="STRING" names="string_output">
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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="Result_143671" type="Result" version="opset1">
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<input>
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<port id="0" precision="STRING">
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<dim>-1</dim>
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</port>
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</input>
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</layer>
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</layers>
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<edges>
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<edge from-layer="0" from-port="0" to-layer="2" to-port="0" />
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<edge from-layer="1" from-port="0" to-layer="3" to-port="0" />
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<edge from-layer="2" from-port="1" to-layer="3" to-port="1" />
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<edge from-layer="3" from-port="2" to-layer="4" to-port="0" />
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<edge from-layer="3" from-port="3" to-layer="4" to-port="1" />
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<edge from-layer="3" from-port="4" to-layer="4" to-port="2" />
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<edge from-layer="4" from-port="3" to-layer="5" to-port="0" />
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</edges>
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<rt_info>
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<eos_token_id value="2" />
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</rt_info>
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</net>
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openvino_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:392979a68e8467eade2841358a65ad574d4718c62b13fe944cb3e58b5854a662
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size 1820902984
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openvino_model.xml
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The diff for this file is too large to render.
See raw diff
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openvino_tokenizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b7b77cf2b305f5fcd17706d2242cec5e69576e6888853fee55fef0c734926605
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size 511582
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openvino_tokenizer.xml
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<?xml version="1.0"?>
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<net name="tokenizer" version="11">
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<layers>
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<layer id="0" name="string_input" type="Parameter" version="opset1">
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<data shape="?" element_type="string" />
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<output>
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<port id="0" precision="STRING" names="string_input">
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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="Constant_143654" type="Const" version="opset1">
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<data element_type="i32" shape="" offset="0" size="4" />
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<output>
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<port id="0" precision="I32" />
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</output>
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</layer>
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18 |
+
<layer id="2" name="Constant_143647" type="Const" version="opset1">
|
19 |
+
<data element_type="u8" shape="511574" offset="4" size="511574" />
|
20 |
+
<output>
|
21 |
+
<port id="0" precision="U8">
|
22 |
+
<dim>511574</dim>
|
23 |
+
</port>
|
24 |
+
</output>
|
25 |
+
</layer>
|
26 |
+
<layer id="3" name="SentencepieceTokenizer_143650" type="SentencepieceTokenizer" version="extension">
|
27 |
+
<data nbest_size="0" alpha="0" add_bos="true" add_eos="false" reverse="false" />
|
28 |
+
<input>
|
29 |
+
<port id="0" precision="U8">
|
30 |
+
<dim>511574</dim>
|
31 |
+
</port>
|
32 |
+
<port id="1" precision="STRING">
|
33 |
+
<dim>-1</dim>
|
34 |
+
</port>
|
35 |
+
</input>
|
36 |
+
<output>
|
37 |
+
<port id="2" precision="I64">
|
38 |
+
<dim>-1</dim>
|
39 |
+
<dim>2</dim>
|
40 |
+
</port>
|
41 |
+
<port id="3" precision="I32">
|
42 |
+
<dim>-1</dim>
|
43 |
+
</port>
|
44 |
+
<port id="4" precision="I64">
|
45 |
+
<dim>2</dim>
|
46 |
+
</port>
|
47 |
+
</output>
|
48 |
+
</layer>
|
49 |
+
<layer id="4" name="Broadcast_143655" type="Broadcast" version="opset3">
|
50 |
+
<data mode="numpy" />
|
51 |
+
<input>
|
52 |
+
<port id="0" precision="I32" />
|
53 |
+
<port id="1" precision="I64">
|
54 |
+
<dim>2</dim>
|
55 |
+
</port>
|
56 |
+
</input>
|
57 |
+
<output>
|
58 |
+
<port id="2" precision="I32">
|
59 |
+
<dim>-1</dim>
|
60 |
+
<dim>-1</dim>
|
61 |
+
</port>
|
62 |
+
</output>
|
63 |
+
</layer>
|
64 |
+
<layer id="5" name="Constant_143656" type="Const" version="opset1">
|
65 |
+
<data element_type="i32" shape="" offset="511578" size="4" />
|
66 |
+
<output>
|
67 |
+
<port id="0" precision="I32" />
|
68 |
+
</output>
|
69 |
+
</layer>
|
70 |
+
<layer id="6" name="ShapeOf_143657" type="ShapeOf" version="opset3">
|
71 |
+
<data output_type="i64" />
|
72 |
+
<input>
|
73 |
+
<port id="0" precision="I32">
|
74 |
+
<dim>-1</dim>
|
75 |
+
</port>
|
76 |
+
</input>
|
77 |
+
<output>
|
78 |
+
<port id="1" precision="I64">
|
79 |
+
<dim>1</dim>
|
80 |
+
</port>
|
81 |
+
</output>
|
82 |
+
</layer>
|
83 |
+
<layer id="7" name="Broadcast_143658" type="Broadcast" version="opset3">
|
84 |
+
<data mode="numpy" />
|
85 |
+
<input>
|
86 |
+
<port id="0" precision="I32" />
|
87 |
+
<port id="1" precision="I64">
|
88 |
+
<dim>1</dim>
|
89 |
+
</port>
|
90 |
+
</input>
|
91 |
+
<output>
|
92 |
+
<port id="2" precision="I32">
|
93 |
+
<dim>-1</dim>
|
94 |
+
</port>
|
95 |
+
</output>
|
96 |
+
</layer>
|
97 |
+
<layer id="8" name="ScatterNDUpdate_143662" type="ScatterNDUpdate" version="opset4">
|
98 |
+
<input>
|
99 |
+
<port id="0" precision="I32">
|
100 |
+
<dim>-1</dim>
|
101 |
+
<dim>-1</dim>
|
102 |
+
</port>
|
103 |
+
<port id="1" precision="I64">
|
104 |
+
<dim>-1</dim>
|
105 |
+
<dim>2</dim>
|
106 |
+
</port>
|
107 |
+
<port id="2" precision="I32">
|
108 |
+
<dim>-1</dim>
|
109 |
+
</port>
|
110 |
+
</input>
|
111 |
+
<output>
|
112 |
+
<port id="3" precision="I32">
|
113 |
+
<dim>-1</dim>
|
114 |
+
<dim>-1</dim>
|
115 |
+
</port>
|
116 |
+
</output>
|
117 |
+
</layer>
|
118 |
+
<layer id="9" name="ScatterNDUpdate_143662" type="Convert" version="opset1">
|
119 |
+
<data destination_type="i64" />
|
120 |
+
<input>
|
121 |
+
<port id="0" precision="I32">
|
122 |
+
<dim>-1</dim>
|
123 |
+
<dim>-1</dim>
|
124 |
+
</port>
|
125 |
+
</input>
|
126 |
+
<output>
|
127 |
+
<port id="1" precision="I64" names="attention_mask">
|
128 |
+
<dim>-1</dim>
|
129 |
+
<dim>-1</dim>
|
130 |
+
</port>
|
131 |
+
</output>
|
132 |
+
</layer>
|
133 |
+
<layer id="11" name="Constant_143651" type="Const" version="opset1">
|
134 |
+
<data element_type="i32" shape="" offset="0" size="4" />
|
135 |
+
<output>
|
136 |
+
<port id="0" precision="I32" />
|
137 |
+
</output>
|
138 |
+
</layer>
|
139 |
+
<layer id="12" name="Broadcast_143652" type="Broadcast" version="opset3">
|
140 |
+
<data mode="numpy" />
|
141 |
+
<input>
|
142 |
+
<port id="0" precision="I32" />
|
143 |
+
<port id="1" precision="I64">
|
144 |
+
<dim>2</dim>
|
145 |
+
</port>
|
146 |
+
</input>
|
147 |
+
<output>
|
148 |
+
<port id="2" precision="I32">
|
149 |
+
<dim>-1</dim>
|
150 |
+
<dim>-1</dim>
|
151 |
+
</port>
|
152 |
+
</output>
|
153 |
+
</layer>
|
154 |
+
<layer id="13" name="ScatterNDUpdate_143653" type="ScatterNDUpdate" version="opset4">
|
155 |
+
<input>
|
156 |
+
<port id="0" precision="I32">
|
157 |
+
<dim>-1</dim>
|
158 |
+
<dim>-1</dim>
|
159 |
+
</port>
|
160 |
+
<port id="1" precision="I64">
|
161 |
+
<dim>-1</dim>
|
162 |
+
<dim>2</dim>
|
163 |
+
</port>
|
164 |
+
<port id="2" precision="I32">
|
165 |
+
<dim>-1</dim>
|
166 |
+
</port>
|
167 |
+
</input>
|
168 |
+
<output>
|
169 |
+
<port id="3" precision="I32">
|
170 |
+
<dim>-1</dim>
|
171 |
+
<dim>-1</dim>
|
172 |
+
</port>
|
173 |
+
</output>
|
174 |
+
</layer>
|
175 |
+
<layer id="14" name="ScatterNDUpdate_143653" type="Convert" version="opset1">
|
176 |
+
<data destination_type="i64" />
|
177 |
+
<input>
|
178 |
+
<port id="0" precision="I32">
|
179 |
+
<dim>-1</dim>
|
180 |
+
<dim>-1</dim>
|
181 |
+
</port>
|
182 |
+
</input>
|
183 |
+
<output>
|
184 |
+
<port id="1" precision="I64" names="input_ids">
|
185 |
+
<dim>-1</dim>
|
186 |
+
<dim>-1</dim>
|
187 |
+
</port>
|
188 |
+
</output>
|
189 |
+
</layer>
|
190 |
+
<layer id="15" name="Result_143663" type="Result" version="opset1">
|
191 |
+
<input>
|
192 |
+
<port id="0" precision="I64">
|
193 |
+
<dim>-1</dim>
|
194 |
+
<dim>-1</dim>
|
195 |
+
</port>
|
196 |
+
</input>
|
197 |
+
</layer>
|
198 |
+
<layer id="10" name="Result_143664" type="Result" version="opset1">
|
199 |
+
<input>
|
200 |
+
<port id="0" precision="I64">
|
201 |
+
<dim>-1</dim>
|
202 |
+
<dim>-1</dim>
|
203 |
+
</port>
|
204 |
+
</input>
|
205 |
+
</layer>
|
206 |
+
</layers>
|
207 |
+
<edges>
|
208 |
+
<edge from-layer="0" from-port="0" to-layer="3" to-port="1" />
|
209 |
+
<edge from-layer="1" from-port="0" to-layer="4" to-port="0" />
|
210 |
+
<edge from-layer="2" from-port="0" to-layer="3" to-port="0" />
|
211 |
+
<edge from-layer="3" from-port="4" to-layer="4" to-port="1" />
|
212 |
+
<edge from-layer="3" from-port="3" to-layer="6" to-port="0" />
|
213 |
+
<edge from-layer="3" from-port="2" to-layer="8" to-port="1" />
|
214 |
+
<edge from-layer="3" from-port="3" to-layer="13" to-port="2" />
|
215 |
+
<edge from-layer="3" from-port="2" to-layer="13" to-port="1" />
|
216 |
+
<edge from-layer="3" from-port="4" to-layer="12" to-port="1" />
|
217 |
+
<edge from-layer="4" from-port="2" to-layer="8" to-port="0" />
|
218 |
+
<edge from-layer="5" from-port="0" to-layer="7" to-port="0" />
|
219 |
+
<edge from-layer="6" from-port="1" to-layer="7" to-port="1" />
|
220 |
+
<edge from-layer="7" from-port="2" to-layer="8" to-port="2" />
|
221 |
+
<edge from-layer="8" from-port="3" to-layer="9" to-port="0" />
|
222 |
+
<edge from-layer="9" from-port="1" to-layer="10" to-port="0" />
|
223 |
+
<edge from-layer="11" from-port="0" to-layer="12" to-port="0" />
|
224 |
+
<edge from-layer="12" from-port="2" to-layer="13" to-port="0" />
|
225 |
+
<edge from-layer="13" from-port="3" to-layer="14" to-port="0" />
|
226 |
+
<edge from-layer="14" from-port="1" to-layer="15" to-port="0" />
|
227 |
+
</edges>
|
228 |
+
<rt_info>
|
229 |
+
<eos_token_id value="2" />
|
230 |
+
</rt_info>
|
231 |
+
</net>
|
special_tokens_map.json
ADDED
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"bos_token": {
|
3 |
+
"content": "<s>",
|
4 |
+
"lstrip": false,
|
5 |
+
"normalized": true,
|
6 |
+
"rstrip": false,
|
7 |
+
"single_word": false
|
8 |
+
},
|
9 |
+
"eos_token": {
|
10 |
+
"content": "</s>",
|
11 |
+
"lstrip": false,
|
12 |
+
"normalized": true,
|
13 |
+
"rstrip": false,
|
14 |
+
"single_word": false
|
15 |
+
},
|
16 |
+
"unk_token": {
|
17 |
+
"content": "<unk>",
|
18 |
+
"lstrip": false,
|
19 |
+
"normalized": true,
|
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.model
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:91b289e85fa20fd375d8b33dc12f77616f18abc6359804471d1fafcb425fecb8
|
3 |
+
size 511574
|
tokenizer_config.json
ADDED
@@ -0,0 +1,42 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"add_bos_token": true,
|
3 |
+
"add_eos_token": false,
|
4 |
+
"add_prefix_space": true,
|
5 |
+
"added_tokens_decoder": {
|
6 |
+
"0": {
|
7 |
+
"content": "<unk>",
|
8 |
+
"lstrip": false,
|
9 |
+
"normalized": true,
|
10 |
+
"rstrip": false,
|
11 |
+
"single_word": false,
|
12 |
+
"special": true
|
13 |
+
},
|
14 |
+
"1": {
|
15 |
+
"content": "<s>",
|
16 |
+
"lstrip": false,
|
17 |
+
"normalized": true,
|
18 |
+
"rstrip": false,
|
19 |
+
"single_word": false,
|
20 |
+
"special": true
|
21 |
+
},
|
22 |
+
"2": {
|
23 |
+
"content": "</s>",
|
24 |
+
"lstrip": false,
|
25 |
+
"normalized": true,
|
26 |
+
"rstrip": false,
|
27 |
+
"single_word": false,
|
28 |
+
"special": true
|
29 |
+
}
|
30 |
+
},
|
31 |
+
"bos_token": "<s>",
|
32 |
+
"clean_up_tokenization_spaces": false,
|
33 |
+
"eos_token": "</s>",
|
34 |
+
"legacy": true,
|
35 |
+
"model_max_length": 2048,
|
36 |
+
"pad_token": null,
|
37 |
+
"sp_model_kwargs": {},
|
38 |
+
"spaces_between_special_tokens": false,
|
39 |
+
"tokenizer_class": "LlamaTokenizer",
|
40 |
+
"unk_token": "<unk>",
|
41 |
+
"use_default_system_prompt": false
|
42 |
+
}
|