Instructions to use Vanbitcase/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vanbitcase/lora_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Vanbitcase/lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download video_preprocessor_config.json from Vanbitcase/lora_model: direct link, hf CLI and curl.
- Browser
- Download file 907 Bytes
-
https://huggingface.co/Vanbitcase/lora_model/resolve/main/video_preprocessor_config.json
- Command line
-
hf download hf://Vanbitcase/lora_model/video_preprocessor_config.json
-
curl -L -o video_preprocessor_config.json https://huggingface.co/Vanbitcase/lora_model/resolve/main/video_preprocessor_config.json
907 Bytes
| { | |
| "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, | |
| "do_sample_frames": false, | |
| "fps": null, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "input_data_format": null, | |
| "max_frames": 768, | |
| "max_pixels": 12845056, | |
| "merge_size": 2, | |
| "min_frames": 4, | |
| "min_pixels": 3136, | |
| "num_frames": null, | |
| "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_metadata": null, | |
| "video_processor_type": "Qwen2VLVideoProcessor" | |
| } | |