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

Libraries

How to use zai-org/LongWriter-llama3.1-8b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="zai-org/LongWriter-llama3.1-8b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("zai-org/LongWriter-llama3.1-8b")
model = AutoModelForCausalLM.from_pretrained("zai-org/LongWriter-llama3.1-8b")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use zai-org/LongWriter-llama3.1-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zai-org/LongWriter-llama3.1-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/LongWriter-llama3.1-8b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/zai-org/LongWriter-llama3.1-8b

SGLang

How to use zai-org/LongWriter-llama3.1-8b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "zai-org/LongWriter-llama3.1-8b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/LongWriter-llama3.1-8b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "zai-org/LongWriter-llama3.1-8b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/LongWriter-llama3.1-8b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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

Not able to run LongWriter-llama3.1-8b-Q8_0-GGUF on Ollama

by deadice97 - opened Aug 26, 2024

Discussion

deadice97

Aug 26, 2024

Hey THUDM, Thanks for this amazing model!
I built the ollama model for the LongWriter-llama3.1-8b-Q8_0-GGUF with the modelfile as below, and it doesn't output answers when run in ollama. Please help me fix this or point out what I am doing wrong. I have very less knowledge of coding, and I mostly will be using these models for academic work. Thanks in advance!

ModelFile contents -

FROM C:/Users/Prajw/.ollama/models/modelsfiles/longwriter/longwriter-llama3.1-8b-q8_0.gguf
PARAMETER temperature 0.5
PARAMETER top_p 0.8
PARAMETER top_k 50
PARAMETER num_ctx 32768
PARAMETER repeat_penalty 1.15
PARAMETER stop USER:
PARAMETER stop ASSISTANT:

TEMPLATE """{{ if .System }}
<>
{{ .System }}
<>
{{ end }}

[INST]{{ index .Messages 0 "Content" }}[/INST]{{ index .Messages 0 "Response" }}
{{ range $i, $msg := .Messages }}
{{- if ne $i 0 -}}
[INST]{{ $msg.Content }}[/INST]{{ $msg.Response }}
{{- end -}}
{{ end }}"""

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