openvino-ci
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Browse files- README.md +55 -0
- config.json +45 -0
- generation_config.json +6 -0
- openvino_detokenizer.bin +3 -0
- openvino_detokenizer.xml +219 -0
- openvino_model.bin +3 -0
- openvino_model.xml +0 -0
- openvino_tokenizer.bin +3 -0
- openvino_tokenizer.xml +943 -0
- special_tokens_map.json +27 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +234 -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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# pythia-2.8b-fp16-ov
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* Model creator: [Eleutherai](https://huggingface.co/EleutherAI)
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* Original model: [pythia-2.8b](https://huggingface.co/EleutherAI/pythia-2.8b)
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## Description
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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/pythia-2.8b-fp16-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 [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/EleutherAI/pythia-2.8b).
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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": "EleutherAI/pythia-2.8b",
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"architectures": [
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"MPTForCausalLM"
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],
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"attn_config": {
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"model_type": ""
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},
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"auto_map": {
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"AutoConfig": "Intel/neural-chat-7b-v1-1--configuration_mpt.MPTConfig",
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"AutoModelForCausalLM": "Intel/neural-chat-7b-v1-1--modeling_mpt.MPTForCausalLM"
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},
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"d_model": 4096,
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"emb_pdrop": 0,
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"embedding_fraction": 1.0,
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"expansion_ratio": 4,
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"init_config": {
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"emb_init_std": null,
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"emb_init_uniform_lim": null,
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"fan_mode": "fan_in",
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"init_div_is_residual": true,
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"init_gain": 0,
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"init_nonlinearity": "relu",
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"init_std": 0.02,
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"name": "kaiming_normal_",
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"verbose": 0
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},
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"init_device": "cpu",
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"learned_pos_emb": true,
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"logit_scale": null,
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"max_seq_len": 2048,
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"model_type": "mpt",
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"n_heads": 32,
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"n_layers": 32,
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"no_bias": true,
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"norm_type": "low_precision_layernorm",
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"resid_pdrop": 0,
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"tokenizer_name": "EleutherAI/gpt-neox-20b",
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"transformers_version": "4.42.4",
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"use_cache": false,
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"verbose": 0,
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"vocab_size": 50279
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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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"eos_token_id": 0,
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"transformers_version": "4.42.4",
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"use_cache": false
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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:eb1aaf54e3666ecdf8dfbf33cbd01af2f1d5d43bc0b96d7ad223a5ba08b63035
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size 558476
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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_253530" 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_253530">
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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_253546" 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_253428" type="Const" version="opset1">
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<data element_type="u8" shape="558427" offset="0" size="558427" />
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<output>
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<port id="0" precision="U8">
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<dim>558427</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_253429" 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>558427</dim>
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</port>
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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_253531" type="VocabDecoder" version="extension">
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<data skip_tokens="0, 1, 50277, 50278" />
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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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<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="CharsToBytes_253532" type="CharsToBytes" 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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<port id="4" 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="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="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="6" name="Constant_253534" type="Const" version="opset1">
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<data element_type="u8" shape="47" offset="558427" size="47" />
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<output>
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<port id="0" precision="U8">
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<dim>47</dim>
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</port>
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</output>
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</layer>
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<layer id="7" name="Constant_253536" type="Const" version="opset1">
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<data element_type="u8" shape="2" offset="558474" size="2" />
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<output>
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<port id="0" precision="U8">
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<dim>2</dim>
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</port>
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</output>
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</layer>
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<layer id="8" name="RegexNormalization_253537" type="RegexNormalization" version="extension">
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<data global_replace="true" />
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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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<port id="3" precision="U8">
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<dim>47</dim>
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</port>
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<port id="4" precision="U8">
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<dim>2</dim>
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</port>
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</input>
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<output>
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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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</port>
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<port id="7" 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="9" name="StringTensorPack_253538" 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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177 |
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|
178 |
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|
179 |
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|
180 |
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|
181 |
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|
182 |
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|
183 |
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|
184 |
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|
185 |
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|
186 |
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|
187 |
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<input>
|
188 |
+
<port id="0" precision="STRING">
|
189 |
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<dim>-1</dim>
|
190 |
+
</port>
|
191 |
+
</input>
|
192 |
+
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|
193 |
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|
194 |
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|
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|
217 |
+
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|
218 |
+
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|
219 |
+
</net>
|
openvino_model.bin
ADDED
@@ -0,0 +1,3 @@
|
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|
1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:cc889e04e387a61d83a35f431decb6d48f6d1a8b5d4eff096e2e978bffe1ff4d
|
3 |
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size 13297451318
|
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 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
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oid sha256:f324126e3d158de43905ff243cdeb10349d1fe4c4683f7cad94c07b8dfa04b90
|
3 |
+
size 1166315
|
openvino_tokenizer.xml
ADDED
@@ -0,0 +1,943 @@
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|
|
1 |
+
<?xml version="1.0"?>
|
2 |
+
<net name="tokenizer" version="11">
|
3 |
+
<layers>
|
4 |
+
<layer id="0" name="Parameter_253340" type="Parameter" version="opset1">
|
5 |
+
<data shape="?" element_type="string" />
|
6 |
+
<output>
|
7 |
+
<port id="0" precision="STRING" names="Parameter_253340">
|
8 |
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<dim>-1</dim>
|
9 |
+
</port>
|
10 |
+
</output>
|
11 |
+
</layer>
|
12 |
+
<layer id="1" name="Constant_253347" type="Const" version="opset1">
|
13 |
+
<data element_type="i64" shape="" offset="0" size="8" />
|
14 |
+
<output>
|
15 |
+
<port id="0" precision="I64" />
|
16 |
+
</output>
|
17 |
+
</layer>
|
18 |
+
<layer id="2" name="StringTensorUnpack_253341" type="StringTensorUnpack" version="extension">
|
19 |
+
<data mode="begins_ends" />
|
20 |
+
<input>
|
21 |
+
<port id="0" precision="STRING">
|
22 |
+
<dim>-1</dim>
|
23 |
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</port>
|
24 |
+
</input>
|
25 |
+
<output>
|
26 |
+
<port id="1" precision="I32">
|
27 |
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<dim>-1</dim>
|
28 |
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</port>
|
29 |
+
<port id="2" precision="I32">
|
30 |
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<dim>-1</dim>
|
31 |
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</port>
|
32 |
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<port id="3" precision="U8">
|
33 |
+
<dim>-1</dim>
|
34 |
+
</port>
|
35 |
+
</output>
|
36 |
+
</layer>
|
37 |
+
<layer id="3" name="NormalizeUnicode_253342" type="NormalizeUnicode" version="extension">
|
38 |
+
<data normalization_form="NFC" />
|
39 |
+
<input>
|
40 |
+
<port id="0" precision="I32">
|
41 |
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<dim>-1</dim>
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42 |
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</port>
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43 |
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<port id="1" precision="I32">
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44 |
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<dim>-1</dim>
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45 |
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</port>
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46 |
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<port id="2" precision="U8">
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47 |
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|
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