How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="askmyteapot/GPT4-X-Alpasta-30b-4bit")
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("askmyteapot/GPT4-X-Alpasta-30b-4bit")
model = AutoModelForCausalLM.from_pretrained("askmyteapot/GPT4-X-Alpasta-30b-4bit", device_map="auto")
Quick Links

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

This is a 4bit quant of https://huggingface.co/MetaIX/GPT4-X-Alpasta-30b

My secret sauce:

  • Using comit 3c16fd9 of 0cc4m's GPTQ fork
  • Using C4 as the calibration dataset
  • Act-order, True-sequential, percdamp 0.1 (the default percdamp is 0.01)
  • No groupsize
  • Will run with CUDA, does not need triton.
  • Quant completed on a 'Premium GPU' and 'High Memory' Google Colab.

Benchmark results

Model C4 WikiText2 PTB
MetaIX's FP16 6.98400259 4.607768536 9.414786339
This Quant 7.292364597 4.954069614 9.754593849
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