Instructions to use DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer", device_map="auto") - NInfer
How to use DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer with NInfer:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer
- SGLang
How to use DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer 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 "DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer" \ --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": "DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer", "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 "DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer" \ --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": "DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer with Docker Model Runner:
docker model run hf.co/DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer
Qwen3.8-27B-Uncensored โ NInfer
This repository contains JonathanColetti/Qwen3.8-27B-Uncensored converted to the native NInfer .ninfer artifact format.
The model weights, architecture, and generation behavior are preserved from the source โ the only change is the container format: the 12-file safetensors distribution (plus the MTP block) is packed into a single self-contained .ninfer artifact for direct use with the NInfer runtime.
Model tree for DogOnKeyboard/Qwen3.8-27B-Uncensored-NInfer
Base model
Qwen/Qwen3.8-27B