Instructions to use Sauten/UAV-CodeAgent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sauten/UAV-CodeAgent with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Sauten/UAV-CodeAgent", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use Sauten/UAV-CodeAgent 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 Sauten/UAV-CodeAgent 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 Sauten/UAV-CodeAgent to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Sauten/UAV-CodeAgent to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Sauten/UAV-CodeAgent", max_seq_length=2048, )
| { | |
| "_valid_kwargs_names": [ | |
| "do_convert_rgb", | |
| "do_resize", | |
| "size", | |
| "size_divisor", | |
| "default_to_square", | |
| "resample", | |
| "do_rescale", | |
| "rescale_factor", | |
| "do_normalize", | |
| "image_mean", | |
| "image_std", | |
| "do_pad", | |
| "do_center_crop", | |
| "crop_size", | |
| "data_format", | |
| "input_data_format", | |
| "device", | |
| "min_pixels", | |
| "max_pixels", | |
| "patch_size", | |
| "temporal_patch_size", | |
| "merge_size" | |
| ], | |
| "crop_size": null, | |
| "data_format": "channels_first", | |
| "default_to_square": true, | |
| "device": null, | |
| "do_center_crop": null, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_pad": null, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "Qwen2VLImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "input_data_format": null, | |
| "max_pixels": 12845056, | |
| "merge_size": 2, | |
| "min_pixels": 3136, | |
| "model_valid_processing_keys": [ | |
| "do_convert_rgb", | |
| "do_resize", | |
| "size", | |
| "size_divisor", | |
| "default_to_square", | |
| "resample", | |
| "do_rescale", | |
| "rescale_factor", | |
| "do_normalize", | |
| "image_mean", | |
| "image_std", | |
| "do_pad", | |
| "do_center_crop", | |
| "crop_size", | |
| "data_format", | |
| "input_data_format", | |
| "device", | |
| "min_pixels", | |
| "max_pixels", | |
| "patch_size", | |
| "temporal_patch_size", | |
| "merge_size" | |
| ], | |
| "patch_size": 14, | |
| "processor_class": "Qwen2_5_VLProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "longest_edge": 12845056, | |
| "shortest_edge": 3136 | |
| }, | |
| "size_divisor": null, | |
| "temporal_patch_size": 2, | |
| "video_processor_type": "Qwen2VLVideoProcessor" | |
| } | |