PEFT
Safetensors
qwen2
lora
unsloth
Generated from Trainer
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use shakedzy/QwQ-32b-Preview-bnb-4bit-wTags with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shakedzy/QwQ-32b-Preview-bnb-4bit-wTags with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use shakedzy/QwQ-32b-Preview-bnb-4bit-wTags 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 shakedzy/QwQ-32b-Preview-bnb-4bit-wTags 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 shakedzy/QwQ-32b-Preview-bnb-4bit-wTags to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for shakedzy/QwQ-32b-Preview-bnb-4bit-wTags to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="shakedzy/QwQ-32b-Preview-bnb-4bit-wTags", max_seq_length=2048, )
QwQ-32B-Preview LoRA for separating thinking/answer parts
This LoRA file was fine-tuned to make QwQ constantly separate its private thoughts from the final answer using <THINKING>...</THINKING><ANSWER>...</ANSWER> tags.
A Q4_K_M GGUF version (which can be used as an adapter for Ollama) is available on shakedzy/QwQ-32B-Preview-with-Tags-LoRA-GGUF.
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