Update README.md

README.md

@@ -6,16 +6,26 @@ datasets:
 
 [gpt2](https://huggingface.co/openai-community/gpt2) quantized to 4-bit using [AutoGPTQ](https://github.com/AutoGPTQ/AutoGPTQ).
 
-To use:
+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/gpt2-AutoGPTQ-4bit-128g"
 model = AutoGPTQForCausalLM.from_quantized(model_name)
-```
+```
+
+
+|Model|4-Bit Perplexity|16-Bit Perplexity|Delta|
+|--|--|--|--|
+|smpanaro/gpt2-AutoGPTQ-4bit-128g|26.5000|25.1875|1.3125|
+|[smpanaro/gpt2-medium-AutoGPTQ-4bit-128g](https://huggingface.co/smpanaro/gpt2-medium-AutoGPTQ-4bit-128g)|19.1719|18.4739|0.698|
+|[smpanaro/gpt2-large-AutoGPTQ-4bit-128g](https://huggingface.co/smpanaro/gpt2-large-AutoGPTQ-4bit-128g)|16.6875|16.4541|0.2334|
+|[smpanaro/gpt2-xl-AutoGPTQ-4bit-128g](https://huggingface.co/smpanaro/gpt2-xl-AutoGPTQ-4bit-128g)|14.9297|14.7951|0.1346|
+<sub>Wikitext perplexity measured as in the [huggingface docs](https://huggingface.co/docs/transformers/en/perplexity)</sub>