Text Generation
Transformers
Safetensors
English
qwen3_moe
programming
code generation
code
coding
coder
chat
brainstorm
qwen
qwen3
qwencoder
brainstorm 20x
creative
all uses cases
Jan-V1
horror
science fiction
fantasy
Star Trek
Star Trek Original
Star Trek The Next Generation
Star Trek Deep Space Nine
Star Trek Voyager
Star Trek Enterprise
Star Trek Discovery.
finetune
thinking
reasoning
unsloth
6x6B
Mixture of Experts
mixture of experts
conversational
Instructions to use DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B") model = AutoModelForMultimodalLM.from_pretrained("DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.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(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B
- SGLang
How to use DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B 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 "DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B" \ --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": "DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B", "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 "DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B" \ --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": "DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Studio
How to use DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B", max_seq_length=2048, ) - Docker Model Runner
How to use DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B with Docker Model Runner:
docker model run hf.co/DavidAU/Qwen3-MOE-6x6B-Star-Trek-Universe-Alpha-256k-ctx-36B