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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("utter-project/TowerVideo-9B") model = AutoModelForMultimodalLM.from_pretrained("utter-project/TowerVideo-9B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from utter-project/TowerVideo-9B: direct link, hf CLI and curl.
- Browser
- Download file 4.24 MB
-
https://huggingface.co/utter-project/TowerVideo-9B/resolve/main/tokenizer.model
- Command line
-
hf download hf://utter-project/TowerVideo-9B/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/utter-project/TowerVideo-9B/resolve/main/tokenizer.model
4.24 MB
- Xet hash:
- fde8653f2f656fb4ab30c2a5db64ba86a916a86134355b76c3bf26a5b022b323
- Size of remote file:
- 4.24 MB
- SHA256:
- 61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
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