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README.md
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## Usage example
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You can use this model with Transformers *pipeline*.
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```python
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model = OVModelForSequenceClassification.from_pretrained(model_id)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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cls_pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
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text = "
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outputs = cls_pipe(text)
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print(outputs)
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```
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Example output:
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```
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[{'label': '
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```
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## Usage example
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To install the requirements for using the OpenVINO backend, do:
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```
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pip install git+https://github.com/huggingface/optimum-intel.git#egg=optimum-intel[openvino]
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```
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This installs all necessary dependencies, including Transformers and OpenVINO.
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*NOTE: Python 3.7-3.9 are supported. A virtualenv is recommended.*
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You can use this model with Transformers *pipeline*.
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```python
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model = OVModelForSequenceClassification.from_pretrained(model_id)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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cls_pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
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text = "OpenVINO is awesome!"
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outputs = cls_pipe(text)
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print(outputs)
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```
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Example output:
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```sh
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[{'label': 'POSITIVE', 'score': 0.9998594522476196}]
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```
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