Instructions to use WpythonW/LoRA-r8-qwen-2.5-VL-slake-XRayModality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WpythonW/LoRA-r8-qwen-2.5-VL-slake-XRayModality with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WpythonW/LoRA-r8-qwen-2.5-VL-slake-XRayModality", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use WpythonW/LoRA-r8-qwen-2.5-VL-slake-XRayModality 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 WpythonW/LoRA-r8-qwen-2.5-VL-slake-XRayModality 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 WpythonW/LoRA-r8-qwen-2.5-VL-slake-XRayModality to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for WpythonW/LoRA-r8-qwen-2.5-VL-slake-XRayModality to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="WpythonW/LoRA-r8-qwen-2.5-VL-slake-XRayModality", max_seq_length=2048, )
- Xet hash:
- 453448436300c48bd7709434f8a4b4a3930ea89b729b34d4e78f7461caca1cbf
- Size of remote file:
- 103 MB
- SHA256:
- 735bb3a8f583744f83b2c306f747e7ea2d0ece9ee90f432c59c8a6dd76c71e5c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.