| language: | |
| - en | |
| license: cc-by-4.0 | |
| library_name: peft | |
| datasets: | |
| - yahma/alpaca-cleaned | |
| metrics: | |
| - accuracy | |
| base_model: meta-llama/Llama-2-70b-hf | |
| This represents the PEFT weights only. The base model is LLaMA 2. Instruction finetuning was done using 4 bit QLoRA on a single A100 GPU with the PEFT config as given below. The dataset used for this instruction finetuning process is a translated version of the cleaned alpaca dataset (translated using NLLB-1.3B). | |
| Do note that this model might have inferior performance on some language specific tasks compared to full finetuning or a different base model trained with more language specific data. | |
| ## 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 |