Instructions to use tiny-random/lfm3-omni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiny-random/lfm3-omni with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForImageTextToText model = AutoModelForImageTextToText.from_pretrained("tiny-random/lfm3-omni", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 706 Bytes
c8adba0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | {
"cap_pixels_per_frame": false,
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"do_sample_frames": true,
"fps": 2.0,
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"max_frames": 384,
"max_video_tokens": 768,
"merge_size": 2,
"min_frames": 4,
"patch_size": 16,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"return_metadata": false,
"size": {
"longest_edge": 25165824,
"shortest_edge": 4096
},
"temporal_patch_size": 2,
"video_processor_type": "Lfm3VlVideoProcessor",
"auto_map": {
"AutoVideoProcessor": "video_processing_lfm3_vl.Lfm3VlVideoProcessor"
}
}
|