Instructions to use AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4") model = AutoModelForMultimodalLM.from_pretrained("AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4
- SGLang
How to use AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4 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 "AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4 with Docker Model Runner:
docker model run hf.co/AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4
is it possible to apply --kv-cache-dtype fp8
Running on dgx spark with the set as per AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-NVFP4
I think you would have to forgo the dflash sliding attention to do this and use MTP instead, you would want to use one of the NVFP4-MTP tagged models from this collection to do so.
Noted. Thanks.
If you want to do even NVFP4 kv cache for even faster speed and 3x capacity gain you can use this model https://huggingface.co/AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-Text-NVFP4-MTP-XS
Combined with my custom bake of vLLM for the DGX Spark that enables a lot of future features that I patched all the bugs out on located here: https://github.com/aeon-7/Gemma-4-26B-A4B-it-Uncensored-NVFP4/pkgs/container/aeon-vllm-ultimate