Create README.md

README.md

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+---
+license: mit
+datasets:
+- wikitext
+---
+
+[pythia-1.4b](https://huggingface.co/EleutherAI/pythia-1.4b) quantized to 4-bit using [AutoGPTQ](https://github.com/AutoGPTQ/AutoGPTQ).
+
+To use, first install AutoGPTQ:
+
+```shell
+pip install auto-gptq
+```
+
+Then load the model from the hub:
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
+
+model_name = "smpanaro/pythia-1.4b-AutoGPTQ-4bit-128g"
+model = AutoGPTQForCausalLM.from_quantized(model_name)
+```
+
+
+|Model|4-Bit Perplexity|16-Bit Perplexity|Delta|
+|--|--|--|--|
+|[smpanaro/pythia-160m-AutoGPTQ-4bit-128g](https://huggingface.co/smpanaro/pythia-160m-AutoGPTQ-4bit-128g)|33.4375|23.3024|10.1351|
+|[smpanaro/pythia-410m-AutoGPTQ-4bit-128g](https://huggingface.co/smpanaro/pythia-410m-AutoGPTQ-4bit-128g)|21.4688|13.9838|7.485|
+|[smpanaro/pythia-1b-AutoGPTQ-4bit-128g](https://huggingface.co/smpanaro/pythia-1b-AutoGPTQ-4bit-128g)|12.0391|11.6178|0.4213|
+|smpanaro/pythia-1.4b-AutoGPTQ-4bit-128g|10.9609|10.4391|0.5218|
+
+
+<sub>Wikitext perplexity measured as in the [huggingface docs](https://huggingface.co/docs/transformers/en/perplexity), lower is better</sub>