Create README.md
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README.md
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---
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license: mit
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datasets:
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- wikitext
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---
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[gpt2-medium](https://huggingface.co/openai-community/gpt2-medium) quantized to 4-bit using [AutoGPTQ](https://github.com/AutoGPTQ/AutoGPTQ).
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To use, first install AutoGPTQ:
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```shell
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pip install auto-gptq
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```
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Then load the model from the hub:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
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model_name = "smpanaro/gpt2-medium-AutoGPTQ-4bit-128g"
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model = AutoGPTQForCausalLM.from_quantized(model_name)
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```
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|Model|4-Bit Perplexity|16-Bit Perplexity|Delta|
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|--|--|--|--|
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|[smpanaro/gpt2-AutoGPTQ-4bit-128g](https://huggingface.co/smpanaro/gpt2-AutoGPTQ-4bit-128g)|26.5000|25.1875|1.3125|
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|smpanaro/gpt2-medium-AutoGPTQ-4bit-128g|19.1719|18.4739|0.698|
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|[smpanaro/gpt2-large-AutoGPTQ-4bit-128g](https://huggingface.co/smpanaro/gpt2-large-AutoGPTQ-4bit-128g)|16.6875|16.4541|0.2334|
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|[smpanaro/gpt2-xl-AutoGPTQ-4bit-128g](https://huggingface.co/smpanaro/gpt2-xl-AutoGPTQ-4bit-128g)|14.9297|14.7951|0.1346|
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<sub>Wikitext perplexity measured as in the [huggingface docs](https://huggingface.co/docs/transformers/en/perplexity)</sub>
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