Instructions to use LLM360/AmberSafe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LLM360/AmberSafe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LLM360/AmberSafe")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LLM360/AmberSafe") model = AutoModelForCausalLM.from_pretrained("LLM360/AmberSafe") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use LLM360/AmberSafe with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LLM360/AmberSafe" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LLM360/AmberSafe", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LLM360/AmberSafe
- SGLang
How to use LLM360/AmberSafe 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 "LLM360/AmberSafe" \ --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": "LLM360/AmberSafe", "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 "LLM360/AmberSafe" \ --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": "LLM360/AmberSafe", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LLM360/AmberSafe with Docker Model Runner:
docker model run hf.co/LLM360/AmberSafe
Commit History
Update README.md f7e5b57 verified
Delete pytorch_model.bin.index.json d57e77e verified
Delete pytorch_model-00003-of-00003.bin c173226 verified
Delete pytorch_model-00002-of-00003.bin 5168d31 verified
Delete pytorch_model-00001-of-00003.bin 6e5ebf5 verified
Upload folder using huggingface_hub 611348d verified
Add link to Q8 checkpoint 6bbda19
Add instructions for Ollama c840bb0
Update README.md d16f8b2
Update README.md ff04781
Update README.md a679926
Update README.md c25a115
Update README.md 2eb5497
Update README.md f23e579
Update README.md 6355444
Update README.md 36e261b
Update README.md 4ef118e
Create README.md 843d8ac
Create README.md 8443d66
add ambersafe model 1ca96df
Richard Fan commited on