commit files to HF hub

README.md

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+---
+language:
+- en
+tags:
+- openvino
+---
+
+# philschmid/roberta-large-sst2
+
+This is the [philschmid/roberta-large-sst2](https://huggingface.co/philschmid/roberta-large-sst2) model converted to [OpenVINO](https://openvino.ai), for accellerated inference.
+
+An example of how to do inference on this model:
+```python
+from optimum.intel.openvino import OVModelForSequenceClassification
+from transformers import AutoTokenizer, pipeline
+
+# model_id should be set to either a local directory or a model available on the HuggingFace hub.
+model_id = "helenai/philschmid-roberta-large-sst2-ov"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = OVModelForSequenceClassification.from_pretrained(model_id)
+pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
+result = pipe("I like you. I love you")
+print(result)
+```
+

config.json

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+{
+  "_name_or_path": "philschmid/roberta-large-sst2",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "negative": "0",
+    "positive": "1"
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.30.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

inference.py

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+from optimum.intel.openvino import OVModelForSequenceClassification
+from transformers import AutoTokenizer, pipeline
+
+# model_id should be set to either a local directory or a model available on the HuggingFace hub.
+model_id = "helenai/philschmid-roberta-large-sst2-ov"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = OVModelForSequenceClassification.from_pretrained(model_id)
+pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
+result = pipe("I like you. I love you")
+print(result)

openvino_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d734570aca1617a616acc1b70f30bfd1449688b4477fde1127b276bcb3710763
+size 1421451440

special_tokens_map.json

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+{
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}