metadata
library_name: transformers
license: other
language:
- ja
π EvoLLM-JP-v1-7B
π€ Models | π Paper | π Blog | π¦ Twitter
EvoLLM-JP-v1-7B is an experimental general-purpose Japanese LLM. This model was created using the Evolutionary Model Merge method. Please refer to our report and blog for more details. This model was produced by merging the following models. We are grateful to the developers of the source models.
Usage
Use the code below to get started with the model.
Click to expand
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
# 1. load model
device = "cuda" if torch.cuda.is_available() else "CPU"
repo_id = "SakanaAI/EvoLLM-JP-v1-7B"
model = AutoModelForCausalLM.from_pretrained(repo_id, torch_dtype="auto")
tokenizer = AutoTokenizer.from_pretrained(repo_id)
model.to(device)
# 2. prepare inputs
text = "ι’θ₯ΏεΌγ§ι’η½γεθ«γθ¨γ£γ¦γΏγ¦δΈγγγ"
messages = [
{"role": "system", "content": "γγͺγγ―ε½Ήη«γ€γεθ¦γγͺγγζ€ι²γγγ¦γγͺγγ’γ·γΉγΏγ³γγ§γγ"},
{"role": "user", "content": text},
]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
# 3. generate
output_ids = model.generate(**inputs.to(device))
output_ids = output_ids[:, inputs.input_ids.shape[1] :]
generated_text = tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0]
print(generated_text)
Model Details
- Developed by: Sakana AI
- Model type: Autoregressive Language Model
- Language(s): Japanese
- License: MICROSOFT RESEARCH LICENSE TERMS (due to the inclusion of the WizardMath model)
- Repository: SakanaAI/evolutionary-model-merge
- Paper: TODO
- Blog: TODO
Acknowledgement
We would like to thank the developers of the source models for their contributions and for making their work available.
Citation
@misc{akiba2024evomodelmerge,
title = {Evolutionary Optimization of Model Merging Recipes},
author. = {Takuya Akiba and Makoto Shing and Yujin Tang and Qi Sun and David Ha},
year = {2024},
eprint = {TODO},
archivePrefix = {arXiv},
primaryClass = {cs.CV}
}