metadata

language:
  - en
  - zh
library_name: transformers
tags:
  - Long Context
  - chatglm
  - llama
datasets:
  - THUDM/LongWriter-6k
pipeline_tag: text-generation

LongWriter-glm4-9b

🤗 [LongWriter Dataset] • 💻 [Github Repo] • 📃 [LongWriter Paper]

LongWriter-glm4-9b is trained based on glm-4-9b, and is capable of generating 10,000+ words at once.

A simple demo for deployment of the model:

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("THUDM/LongWriter-glm4-9b", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("THUDM/LongWriter-glm4-9b", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
model = model.eval()
query = "Write a 10000-word China travel guide"
response, history = model.chat(tokenizer, query, history=[], max_new_tokens=32768, temperature=0.5)
print(response)

Environment: Same environment requirement as glm-4-9b-chat (transforemrs>=4.44.0).

License: glm-4-9b License

Citation

If you find our work useful, please consider citing LongWriter:

@article{bai2024longwriter,
  title={LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs}, 
  author={Yushi Bai and Jiajie Zhang and Xin Lv and Linzhi Zheng and Siqi Zhu and Lei Hou and Yuxiao Dong and Jie Tang and Juanzi Li},
  journal={arXiv preprint arXiv:2408.07055},
  year={2024}
}