Instructions to use unsloth/Qwen3-VL-4B-Thinking-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use unsloth/Qwen3-VL-4B-Thinking-FP8 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 unsloth/Qwen3-VL-4B-Thinking-FP8 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 unsloth/Qwen3-VL-4B-Thinking-FP8 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/Qwen3-VL-4B-Thinking-FP8 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="unsloth/Qwen3-VL-4B-Thinking-FP8", max_seq_length=2048, )
- Xet hash:
- 9ff8f0fd4c2833b00cfea1352feea937c5b574081b631d1ebbd102b133731524
- Size of remote file:
- 654 MB
- SHA256:
- be6fe6b2564e3211acf15427244662973e37c9b872cfdf130ed9d1917bb20dfa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.