commit files to HF hub
Browse files- README.md +25 -0
- config.json +27 -0
- inference.py +10 -0
- merges.txt +0 -0
- openvino_model.bin +3 -0
- openvino_model.xml +0 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +57 -0
- vocab.json +0 -0
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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# textattack/roberta-base-SST-2
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This is the [textattack/roberta-base-SST-2](https://huggingface.co/textattack/roberta-base-SST-2) 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 OVModelForSequenceClassification
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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/textattack-roberta-base-SST-2-ov"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = OVModelForSequenceClassification.from_pretrained(model_id)
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pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
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result = pipe("I like you. I love you")
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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": "textattack/roberta-base-SST-2",
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"architectures": [
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"RobertaForSequenceClassification"
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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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"finetuning_task": "sst-2",
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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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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"transformers_version": "4.36.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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inference.py
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from optimum.intel.openvino import OVModelForSequenceClassification
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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/textattack-roberta-base-SST-2-ov"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = OVModelForSequenceClassification.from_pretrained(model_id)
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pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
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result = pipe("I like you. I love you")
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print(result)
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merges.txt
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openvino_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:236b67d149d9890011c51445f53e81592d93d5d9dc493bb402c1423296d82d60
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size 498592984
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openvino_model.xml
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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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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"cls_token": {
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"content": "<s>",
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"lstrip": false,
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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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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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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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"mask_token": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<pad>",
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"lstrip": false,
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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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"sep_token": {
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"content": "</s>",
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"lstrip": false,
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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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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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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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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"added_tokens_decoder": {
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"0": {
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"3": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"50264": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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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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"eos_token": "</s>",
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"errors": "replace",
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"mask_token": "<mask>",
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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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"tokenizer_class": "RobertaTokenizer",
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"trim_offsets": true,
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"unk_token": "<unk>"
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}
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vocab.json
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