Instructions to use QuantFactory/LongWriter-llama3.1-8b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/LongWriter-llama3.1-8b-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("QuantFactory/LongWriter-llama3.1-8b-GGUF", dtype="auto")

llama-cpp-python

How to use QuantFactory/LongWriter-llama3.1-8b-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/LongWriter-llama3.1-8b-GGUF",
	filename="LongWriter-llama3.1-8b.Q2_K.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use QuantFactory/LongWriter-llama3.1-8b-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/LongWriter-llama3.1-8b-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M
```

Unsloth Studio new

How to use QuantFactory/LongWriter-llama3.1-8b-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for QuantFactory/LongWriter-llama3.1-8b-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for QuantFactory/LongWriter-llama3.1-8b-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/LongWriter-llama3.1-8b-GGUF to start chatting

Docker Model Runner
How to use QuantFactory/LongWriter-llama3.1-8b-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/LongWriter-llama3.1-8b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/LongWriter-llama3.1-8b-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.LongWriter-llama3.1-8b-GGUF-Q4_K_M

List all available models

lemonade list

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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GGUF

Model size

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Architecture

llama

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Dataset used to train QuantFactory/LongWriter-llama3.1-8b-GGUF

Paper for QuantFactory/LongWriter-llama3.1-8b-GGUF

LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs

Paper • 2408.07055 • Published Aug 13, 2024 • 69