This repo contains a low-rank adapter for CALM fit on the dataset specially extracted from llm-japanese-dataset.
You can test this at https://huggingface.co/spaces/izumi-lab/stormy-7b-10ep
This version of the weights was trained with the following hyperparameters:
- Epochs: 10
- Batch size: 128
- Cutoff length: 300
- Learning rate: 3e-4
- Lora r: 4
- Lora target modules: query_key_value
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base_model = "cyberagent/open-calm-7b"
model = AutoModelForCausalLM.from_pretrained(base_model, torch_dtype=torch.float16)
tokenizer = AutoTokenizer.from_pretrained(base_model)
model = PeftModel.from_pretrained(
model,
"izumi-lab/stormy-7b-10ep",
torch_dtype=torch.float16,
)
To see more latest information, please go to llm.msuzuki.me.
Details
- Japanese Paper:
- English Paper:
- Website: llm.msuzuki.me.
Citation: TBD
If you have any inquiries, such as joint research, data provision, various types of support, please email izumi-llm@socsim.org .