Text Generation
Transformers
Safetensors
English
qwen2
chat
abliterated
uncensored
conversational
text-generation-inference
Instructions to use huihui-ai/QwQ-32B-abliterated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huihui-ai/QwQ-32B-abliterated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="huihui-ai/QwQ-32B-abliterated") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("huihui-ai/QwQ-32B-abliterated") model = AutoModelForCausalLM.from_pretrained("huihui-ai/QwQ-32B-abliterated", device_map="auto") 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]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use huihui-ai/QwQ-32B-abliterated with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "huihui-ai/QwQ-32B-abliterated" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "huihui-ai/QwQ-32B-abliterated", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/huihui-ai/QwQ-32B-abliterated
- SGLang
How to use huihui-ai/QwQ-32B-abliterated 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 "huihui-ai/QwQ-32B-abliterated" \ --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": "huihui-ai/QwQ-32B-abliterated", "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 "huihui-ai/QwQ-32B-abliterated" \ --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": "huihui-ai/QwQ-32B-abliterated", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use huihui-ai/QwQ-32B-abliterated with Docker Model Runner:
docker model run hf.co/huihui-ai/QwQ-32B-abliterated
Great job on this! Thank you!!
#5
by Codeicidal - opened
Since your last update this is my new favourite model, it never refuses!
Are you planning on attempting to abliterate Gemma 3 ?
Codeicidal changed discussion status to closed
Codeicidal changed discussion status to open
gemma3 27b?
Thanks for your Abliterated LLM models! Of all the Abliterated models I’ve tested, yours are by far the best. I can’t wait for the 12B and 27B versions of Gemma 3!