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:
- 9781582ccf3dca42c7c4e9cbfd759014a3dc04775c04d7c9461b24b75bcfc7b4
- Size of remote file:
- 3.9 GB
- SHA256:
- 2ca2d9db3a941cb62f30e02df83923b696c541e09e25ab7000d061566e6c5a92
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