  from transformers import AutoModelForCausalLM, AutoTokenizer
  model_name = "EleutherAI/pythia-2.8b-deduped"
  model = AutoModelForCausalLM.from_pretrained(model_name)
  tokenizer = AutoTokenizer.from_pretrained(model_name)
  from auto_round import AutoRound
  bits, group_size, sym = 4, 128, False
  autoround = AutoRound(model, tokenizer, nsamples=128, iters=200, seqlen=512, batch_size=4, bits=bits, group_size=group_size, sym=sym)
  autoround.quantize()
  output_dir = "./AutoRound/EleutherAI_pythia-2.8b-deduped-autoround-int4-gs128-asym"
  autoround.save_quantized(output_dir, format='auto_round', inplace=True)

License

Apache 2.0 License

Disclaimer

This quantized model comes with no warranty. It has been developed only for research purposes.

fbaldassarri/EleutherAI_pythia-2.8b-deduped-autoround-int4-gs128-asym

Model Information

Replication Recipe

Step 1 Install Requirements

Step 2 Build Intel AutoRound wheel from sources

Step 3 Script for Quantization

License

Disclaimer

fbaldassarri/
EleutherAI_pythia-2.8b-deduped-autoround-int4-gs128-asym