Instructions to use AskVenice/venice-uncensored with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AskVenice/venice-uncensored with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AskVenice/venice-uncensored")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AskVenice/venice-uncensored", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AskVenice/venice-uncensored with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AskVenice/venice-uncensored" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AskVenice/venice-uncensored", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AskVenice/venice-uncensored
- SGLang
How to use AskVenice/venice-uncensored 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 "AskVenice/venice-uncensored" \ --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": "AskVenice/venice-uncensored", "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 "AskVenice/venice-uncensored" \ --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": "AskVenice/venice-uncensored", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AskVenice/venice-uncensored with Docker Model Runner:
docker model run hf.co/AskVenice/venice-uncensored
- Xet hash:
- 64fe8a4d97667952ea01dccbf6f385aced3ec0436f83bfff0cc2dc6ce3b6a281
- Size of remote file:
- 4.78 GB
- SHA256:
- fe7482606e12f4e72cb6e3d2e4f7a039d63d103ee4005e5c7a34c78d5dbae37f
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