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--- |
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language: en |
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license: apache-2.0 |
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datasets: |
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- sst2 |
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- glue |
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metrics: |
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- accuracy |
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tags: |
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- text-classfication |
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- int8 |
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--- |
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# Dynamically quantized DistilBERT base uncased finetuned SST-2 |
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## Table of Contents |
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- [Model Details](#model-details) |
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- [How to Get Started With the Model](#how-to-get-started-with-the-model) |
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## Model Details |
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**Model Description:** This model is a [DistilBERT](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) fine-tuned on SST-2 dynamically quantized with [optimum-intel](https://github.com/huggingface/optimum-intel) through the usage of [Intel® Neural Compressor](https://github.com/intel/neural-compressor). |
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- **Model Type:** Text Classification |
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- **Language(s):** English |
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- **License:** Apache-2.0 |
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- **Parent Model:** For more details on the original model, we encourage users to check out [this](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) model card. |
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## How to Get Started With the Model |
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To load the quantized model, you can do as follows: |
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```python |
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from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSequenceClassification |
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model = IncQuantizedModelForSequenceClassification.from_pretrained("Intel/distilbert-base-uncased-finetuned-sst-2-english-int8-dynamic") |
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``` |
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