Instructions to use beanham/qwen3_8b.implicit_l14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beanham/qwen3_8b.implicit_l14 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("beanham/qwen3_8b.implicit_l14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download video_preprocessor_config.json from beanham/qwen3_8b.implicit_l14: direct link, hf CLI and curl.
- Browser
- Download file 817 Bytes
-
https://huggingface.co/beanham/qwen3_8b.implicit_l14/resolve/main/video_preprocessor_config.json
- Command line
-
hf download hf://beanham/qwen3_8b.implicit_l14/video_preprocessor_config.json
-
curl -L -o video_preprocessor_config.json https://huggingface.co/beanham/qwen3_8b.implicit_l14/resolve/main/video_preprocessor_config.json
817 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_rescale": true, | |
| "do_resize": true, | |
| "do_sample_frames": true, | |
| "fps": 2, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "input_data_format": null, | |
| "max_frames": 768, | |
| "merge_size": 2, | |
| "min_frames": 4, | |
| "num_frames": null, | |
| "pad_size": null, | |
| "patch_size": 16, | |
| "processor_class": "Qwen3VLProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "return_metadata": false, | |
| "size": { | |
| "longest_edge": 25165824, | |
| "shortest_edge": 4096 | |
| }, | |
| "temporal_patch_size": 2, | |
| "video_metadata": null, | |
| "video_processor_type": "Qwen3VLVideoProcessor" | |
| } | |