Video-Text-to-Text
Transformers
Safetensors
llava_onevision
image-text-to-text
multimodal
multilingual
vlm
translation
Instructions to use utter-project/TowerVideo-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use utter-project/TowerVideo-9B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("utter-project/TowerVideo-9B") model = AutoModelForImageTextToText.from_pretrained("utter-project/TowerVideo-9B") - Notebooks
- Google Colab
- Kaggle
File size: 753 Bytes
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"crop_size": null,
"data_format": "channels_first",
"default_to_square": false,
"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": [
0.5,
0.5,
0.5
],
"image_processor_type": "SiglipImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"input_data_format": null,
"num_frames": null,
"processor_class": "LlavaOnevisionProcessor",
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 384,
"width": 384
},
"size_divisor": null,
"video_metadata": null,
"video_processor_type": "LlavaOnevisionVideoProcessor"
}
|