Quantized LLaMA2

quantized-llama2-alpaca is a fine-tuned version of the LLaMA2 (Llama-2-7b-hf) model on the Alpaca dataset using QLoRA.

Training procedure

The following bitsandbytes quantization config was used during training:

  • load_in_8bit: False
  • load_in_4bit: True
  • llm_int8_threshold: 6.0
  • llm_int8_skip_modules: None
  • llm_int8_enable_fp32_cpu_offload: False
  • llm_int8_has_fp16_weight: False
  • bnb_4bit_quant_type: nf4
  • bnb_4bit_use_double_quant: True
  • bnb_4bit_compute_dtype: bfloat16

Framework versions

  • PEFT 0.4.0
Downloads last month
5
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for NouRed/quantized-llama2-alpaca

Adapter
(1760)
this model

Dataset used to train NouRed/quantized-llama2-alpaca