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gpt4-alpaca-lora-30B-GGML

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metadata
license: other
language:
  - en
pipeline_tag: text2text-generation
tags:
  - alpaca
  - llama
  - chat
  - gpt4
inference: false

GPT4 Alpaca LoRA 30B - 4bit GGML

This is a 4-bit GGML 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, producing unquantised model GPT4-Alpaca-LoRA-30B-HF

The files in this repo were then quantized to 4bit and 5bit for use with llama.cpp.

REQUIRES LATEST LLAMA.CPP (May 12th 2023 - commit b9fd7ee)!

llama.cpp recently made a breaking change to its quantisation methods.

I have re-quantised the GGML files in this repo. Therefore you will require llama.cpp compiled on May 12th or later (commit b9fd7ee or later) to use them.

The previous files, which will still work in older versions of llama.cpp, can be found in branch previous_llama.

Provided files

Name Quant method Bits Size RAM required Use case
gpt4-alpaca-lora-30B.ggml.q4_0.bin q4_0 4bit 20.3GB 23GB 4bit.
gpt4-alpaca-lora-30B.ggml.q5_0.bin q5_0 5bit 22.4GB 25GB 5bit. Higher accuracy, higher resource usage, slower inference.
gpt4-alpaca-lora-30B.ggml.q5_1.bin q5_1 5bit 24.4GB 27GB 5bit. Even higher accuracy and resource usage, and slower inference.

How to run in llama.cpp

I use the following command line; adjust for your tastes and needs:

./main -t 18 -m gpt4-alpaca-lora-30B.GGML.q4_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
Write a story about llamas
### Response:"

Change -t 18 to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use -t 8.

If you want to have a chat-style conversation, replace the -p <PROMPT> argument with -i -ins

How to run in text-generation-webui

Create a model directory that has ggml (case sensitive) in its name. Then put the desired .bin file in that model directory.

Further instructions here: text-generation-webui/docs/llama.cpp-models.md.

Note that as of May 12th, text-gen-ui likely won't support the newly updated GGML models until it's been updated.

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.