Instructions to use Pclanglais/Brahe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pclanglais/Brahe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Pclanglais/Brahe")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Pclanglais/Brahe") model = AutoModelForCausalLM.from_pretrained("Pclanglais/Brahe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Pclanglais/Brahe with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Pclanglais/Brahe" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pclanglais/Brahe", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Pclanglais/Brahe
- SGLang
How to use Pclanglais/Brahe 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 "Pclanglais/Brahe" \ --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": "Pclanglais/Brahe", "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 "Pclanglais/Brahe" \ --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": "Pclanglais/Brahe", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Pclanglais/Brahe with Docker Model Runner:
docker model run hf.co/Pclanglais/Brahe
Commit History
-
Update README.md
Verified signature659bbbd
-
Update README.md
234ad26 -
Update README.md
e6eb213
-
Update README.md
699cc46 -
Update README.md
a8bd1c5 -
Update README.md
2ad1a92 -
Update README.md
5cb88e8
-
Upload with huggingface_hub
0f1a885 -
Delete config.json
f3107f8 -
Delete model-00003-of-00003.safetensors
e6c928e -
Delete model-00002-of-00003.safetensors
5cb7ab6 -
Delete model-00001-of-00003.safetensors
7905783 -
Upload with huggingface_hub
3cbf81c -
Upload model-00003-of-00003.safetensors with huggingface_hub
b14154b -
Upload tokenizer
928d4b0 -
Upload folder using huggingface_hub
57be5c3 -
Delete model-00003-of-00003.safetensors
6028ef1 -
Delete model-00002-of-00003.safetensors
5622216 -
Delete model-00001-of-00003.safetensors
e451dcd -
Delete brahe_instructions.json
58c1e92 -
Update README.md
97117ec -
Update README.md
84b0dca -
Update README.md
4e34fb1 -
Upload tokenizer
687a6ca -
Upload folder using huggingface_hub
ccccd1b
-
Upload brahe_instructions.json
c6b302a
-
Update README.md
cbbd4d1 -
Update README.md
76ef35c
-
Update README.md
6a0cd0a -
Update README.md
ab065b3 -
Update README.md
88a0bec -
Update README.md
b6f714f -
Update README.md
e59b000 -
Update README.md
87365be -
Update README.md
d357a85 -
Update README.md
74a77c4 -
Update README.md
de3e322 -
Update README.md
adding examples005b2ba -
Update README.md
50da743 -
Update README.md
e4c3308 -
Update README.md
558301d -
Update README.md
7849dac -
Update README.md
0312ca1 -
Upload folder using huggingface_hub
ec202fd -
Update README.md
+ model card for Brahe96ede02 -
initial commit
Pierre-Carl Langlais623439f