QuantFactory/LongWriter-llama3.1-8b-GGUF
This is quantized version of THUDM/LongWriter-llama3.1-8b created using llama.cpp
Original Model Card
LongWriter-llama3.1-8b
🤗 [LongWriter Dataset] • 💻 [Github Repo] • 📃 [LongWriter Paper]
LongWriter-llama3.1-8b is trained based on Meta-Llama-3.1-8B, 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-llama3.1-8b", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("THUDM/LongWriter-llama3.1-8b", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
model = model.eval()
query = "Write a 10000-word China travel guide"
prompt = f"[INST]{query}[/INST]"
input = tokenizer(prompt, truncation=False, return_tensors="pt").to(device)
context_length = input.input_ids.shape[-1]
output = model.generate(
**input,
max_new_tokens=32768,
num_beams=1,
do_sample=True,
temperature=0.5,
)[0]
response = tokenizer.decode(output[context_length:], skip_special_tokens=True)
print(response)
Please ahere to the prompt template (system prompt is optional): <<SYS>>\n{system prompt}\n<</SYS>>\n\n[INST]{query1}[/INST]{response1}[INST]{query2}[/INST]{response2}...
License: Llama-3.1 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}
}
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