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smpanaro/gpt2-xl-AutoGPTQ-4bit-128g
gpt2-xl-AutoGPTQ-4bit-128g is a text generation model from smpanaro. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
gpt2-xl quantized to 4-bit using AutoGPTQ.
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From the Hugging Face model README
gpt2-xl quantized to 4-bit using AutoGPTQ.
To use, first install AutoGPTQ:
pip install auto-gptq
Then load the model from the hub:
from transformers import AutoModelForCausalLM, AutoTokenizer
from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
model_name = "smpanaro/gpt2-xl-AutoGPTQ-4bit-128g"
model = AutoGPTQForCausalLM.from_quantized(model_name, use_triton=True)
# Note: despite this model being quantized only using groups and desc_act=False, Triton still seems to be required.
| 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 | 19.1719 | 18.4739 | 0.698 |
| smpanaro/gpt2-large-AutoGPTQ-4bit-128g | 16.6875 | 16.4541 | 0.2334 |
| smpanaro/gpt2-xl-AutoGPTQ-4bit-128g | 14.9297 | 14.7951 | 0.1346 |
| <sub>Wikitext perplexity measured as in the huggingface docs, lower is better</sub> |