metadata
license: cc-by-sa-4.0
datasets:
- izumi-lab/llm-japanese-dataset
language:
- ja
tags:
- llama
- causal-lm
This repo contains a low-rank adapter for LLaMA-7b fit on the llm-japanese-dataset dataset.
This version of the weights was trained with the following hyperparameters:
- Epochs: 5
- Batch size: 128
- Cutoff length: 256
- Learning rate: 3e-4
- Lora r: 4
- Lora target modules: q_proj, v_proj
import torch
from transformers import LlamaForCausalLM, LlamaTokenizer
from peft import PeftModel
base_model = "decapoda-research/llama-7b-hf"
# Please note that the special license of decapoda-research/llama-7b-hf is applied.
model = LlamaForCausalLM.from_pretrained(base_model, torch_dtype=torch.float16)
tokenizer = LlamaTokenizer.from_pretrained(base_model)
model = PeftModel.from_pretrained(
model,
"izumi-lab/llama-7b-japanese-lora-v0",
torch_dtype=torch.float16,
)
To see more latest information, please go to llm.msuzuki.me.
Details
- Japanese Paper: https://jxiv.jst.go.jp/index.php/jxiv/preprint/view/422
- English Paper:
- GitHub: [https://github.com/retarfi/jallm]
- Website: llm.msuzuki.me.
Citation:
If you have any inquiries, such as joint research, data provision, various types of support, please email to [email protected] .