commit files to HF hub
Browse files- .gitattributes +1 -0
- README.md +25 -0
- config.json +30 -0
- inference.py +10 -0
- openvino_model.bin +3 -0
- openvino_model.xml +0 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +9 -0
- tokenizer.json +3 -0
- tokenizer_config.json +22 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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language:
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- en
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tags:
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- openvino
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---
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# deepset/xlm-roberta-base-squad2
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This is the [deepset/xlm-roberta-base-squad2](https://huggingface.co/deepset/xlm-roberta-base-squad2) model converted to [OpenVINO](https://openvino.ai), for accellerated inference.
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An example of how to do inference on this model:
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```python
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from optimum.intel.openvino import OVModelForQuestionAnswering
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from transformers import AutoTokenizer, pipeline
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# model_id should be set to either a local directory or a model available on the HuggingFace hub.
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model_id = "helenai/deepset-xlm-roberta-base-squad2-ov"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = OVModelForQuestionAnswering.from_pretrained(model_id)
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pipe = pipeline("question-answering", model=model, tokenizer=tokenizer)
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result = pipe("What is OpenVINO?", "OpenVINO is a framework that accelerates deep learning inferencing")
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print(result)
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```
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config.json
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{
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"_name_or_path": "deepset/xlm-roberta-base-squad2",
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"architectures": [
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"XLMRobertaForQuestionAnswering"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"language": "english",
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "xlm-roberta",
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"name": "XLMRoberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_past": true,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"transformers_version": "4.30.2",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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inference.py
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from optimum.intel.openvino import OVModelForQuestionAnswering
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from transformers import AutoTokenizer, pipeline
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# model_id should be set to either a local directory or a model available on the HuggingFace hub.
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model_id = "helenai/deepset-xlm-roberta-base-squad2-ov"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = OVModelForQuestionAnswering.from_pretrained(model_id)
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pipe = pipeline("question-answering", model=model, tokenizer=tokenizer)
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result = pipe("What is OpenVINO?", "OpenVINO is a framework that accelerates deep learning inferencing")
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print(result)
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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:b76a8314d94761f36ebc568daae56f5f712ee1efb31d7251387a976041c84e25
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size 1109822656
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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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sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
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size 5069051
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special_tokens_map.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": "<mask>",
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"unk_token": "<unk>"
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:2bae0289b9bb66bfbf85d834f6313ebd8e40f484df2bd0351539e74a0e4ddeb4
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size 17098081
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tokenizer_config.json
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{
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"cls_token": "<s>",
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"do_lower_case": false,
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"eos_token": "</s>",
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"full_tokenizer_file": null,
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"mask_token": {
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"__type": "AddedToken",
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"model_max_length": 512,
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"sp_model_kwargs": {},
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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