Instructions to use OpenAssistant/falcon-40b-sft-top1-560 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenAssistant/falcon-40b-sft-top1-560 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OpenAssistant/falcon-40b-sft-top1-560", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("OpenAssistant/falcon-40b-sft-top1-560", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OpenAssistant/falcon-40b-sft-top1-560 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenAssistant/falcon-40b-sft-top1-560" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenAssistant/falcon-40b-sft-top1-560", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OpenAssistant/falcon-40b-sft-top1-560
- SGLang
How to use OpenAssistant/falcon-40b-sft-top1-560 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 "OpenAssistant/falcon-40b-sft-top1-560" \ --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": "OpenAssistant/falcon-40b-sft-top1-560", "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 "OpenAssistant/falcon-40b-sft-top1-560" \ --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": "OpenAssistant/falcon-40b-sft-top1-560", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OpenAssistant/falcon-40b-sft-top1-560 with Docker Model Runner:
docker model run hf.co/OpenAssistant/falcon-40b-sft-top1-560
- Xet hash:
- a56dea220cb325a333a2111ee2c7357aa5e7aa839f3ba8644b8508aeb846d60c
- Size of remote file:
- 9.51 GB
- SHA256:
- 4c715b854bfeb6b48794dbdcff5159aa60d412a2e0e526a394e9daeb6dfa7ce2
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