LongWriter-glm4-9b#
README(From Huggingface)#
language:
en
zh library_name: transformers tags:
Long Context
chatglm
llama datasets: train:
AI-ModelScope/LongWriter-6k pipeline_tag: text-generation studios:
ZhipuAI/LongWriter-glm4-9b-demo
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 paddlenlp.transformers import AutoTokenizer, AutoModelForCausalLM
import paddle
tokenizer = AutoTokenizer.from_pretrained("ZhipuAI/LongWriter-glm4-9b", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("ZhipuAI/LongWriter-glm4-9b", dtype=paddle.bfloat16, trust_remote_code=True, )
model = model.eval()
query = "Write a `10000`-word China travel guide"
response, history = model.chat(tokenizer, query, history=[], max_new_tokens=1024, temperature=0.5)
print(response)
Environment: transformers==4.43.0
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}
}
Model Files#
README.md (1.7 KB)
config.json (1.4 KB)
configuration_chatglm.py (2.2 KB)
generation_config.json (120.0 B)
model-00001-of-00004.safetensors (4.6 GB)
model-00002-of-00004.safetensors (4.6 GB)
model-00003-of-00004.safetensors (4.6 GB)
model-00004-of-00004.safetensors (3.7 GB)
model.safetensors.index.json (28.1 KB)
modeling_chatglm.py (43.4 KB)
special_tokens_map.json (35.0 B)
tokenization_chatglm.py (10.7 KB)
tokenizer.model (2.5 MB)
tokenizer_config.json (843.0 B)