| language: en | |
| license: apache-2.0 | |
| datasets: | |
| - sst2 | |
| - glue | |
| tags: | |
| - openvino | |
| ## distilbert-base-uncased-finetuned-sst-2-english | |
| [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) quantized with NNCF PTQ and exported to the OpenVINO IR. | |
| **Model Description:** l is This model reaches an accuracy of 90.0 on the validation set. See [ov\_config.json](./ov_config.json) for the quantization config. | |
| ## Usage example | |
| You can use this model with Transformers *pipeline*. | |
| ```python | |
| from transformers import AutoTokenizer, pipeline | |
| from optimum.intel.openvino import OVModelForSequenceClassification | |
| model_id = "helenai/distilbert-base-uncased-finetuned-sst-2-english-ov-int8" | |
| model = OVModelForSequenceClassification.from_pretrained(model_id) | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| cls_pipe = pipeline("text-classification", model=model, tokenizer=tokenizer) | |
| text = "He's a dreadful magician." | |
| outputs = cls_pipe(text) | |
| print(outputs) | |
| ``` | |
| Example output: | |
| ```bash | |
| [{'label': 'NEGATIVE', 'score': 0.9929909706115723}] | |
| ``` | |