iamshnoo/alpaca-2-70b-hindi

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:

• —loadin8bit: False
• —loadin4bit: True
• —llmint8threshold: 6.0
• —llmint8skip_modules: None
• —llmint8enablefp32cpu_offload: False
• —llmint8hasfp16weight: False
• —bnb4bitquant_type: nf4
• —bnb4bitusedoublequant: True
• —bnb4bitcompute_dtype: bfloat16

Framework versions

• —PEFT 0.4.0