This is a pre-merged version of the Chansung GPT4 Alpaca 30B LoRA model.
It was created by merging the LoRA provided in the above repo with the original Llama 30B model.
You will need at least 60GB VRAM to use this model.
For a GPTQ quantized 4bit model, usable on a 24GB GPU, see: GPT4-Alpaca-LoRA-30B-GPTQ-4bit-128g
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Thanks, and how to contribute.
Thanks to the chirper.ai team!
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Original GPT4 Alpaca Lora model card
This repository comes with LoRA checkpoint to make LLaMA into a chatbot like language model. The checkpoint is the output of instruction following fine-tuning process with the following settings on 8xA100(40G) DGX system.
- Training script: borrowed from the official Alpaca-LoRA implementation
- Training script:
python finetune.py \
--base_model='decapoda-research/llama-30b-hf' \
--data_path='alpaca_data_gpt4.json' \
--num_epochs=10 \
--cutoff_len=512 \
--group_by_length \
--output_dir='./gpt4-alpaca-lora-30b' \
--lora_target_modules='[q_proj,k_proj,v_proj,o_proj]' \
--lora_r=16 \
--batch_size=... \
--micro_batch_size=...
You can find how the training went from W&B report here.