Text Generation
Transformers
Safetensors
qwen3_5
image-text-to-text
qwen3.6
qwopus
gptq
gptq-pro
marlin
vllm
int4
quantized
mmlu-pro
24-may-update
conversational
4-bit precision
Instructions to use XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1") 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("XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1") model = AutoModelForMultimodalLM.from_pretrained("XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1", device_map="auto") 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 XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1
- SGLang
How to use XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1 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 "XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1" \ --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": "XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1", "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 "XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1" \ --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": "XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1 with Docker Model Runner:
docker model run hf.co/XReyRobert/Qwopus3.6-27B-v2-GPTQ-Pro-v1
Commit History
Remove unpublished custom image target from card 66caaae verified
Clarify custom vLLM image scope 8fb3cbd verified
Document vLLM deployment image for reproducibility 15b501e verified
Align support buttons in model card 46a8c29 verified
Add support button to model card f9c945f verified
Restore X follow button e8845bf verified
Remove misplaced 35B runtime image from 27B card 4e8de53 verified
Add Qwopus3.6-35B-A3B runtime image to model card a03e47e verified
Clarify Terminal-Bench protocol settings 6e0077f
Xavier Rey-Robert commited on
Update Qwen Terminal-Bench comparison table 3b1639f
Xavier Rey-Robert commited on
Fix Qwen Terminal-Bench 2.0 comparison 2c59376
Xavier Rey-Robert commited on
Add Qwen Terminal-Bench comparison 82f2c89
Xavier Rey-Robert commited on
Add Terminal-Bench 2.0 evaluation report 898a3f9
Xavier Rey-Robert commited on