Video-Text-to-Text
Transformers
Safetensors
llava_onevision
image-text-to-text
multimodal
multilingual
vlm
translation
Instructions to use utter-project/TowerVideo-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use utter-project/TowerVideo-2B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("utter-project/TowerVideo-2B") model = AutoModelForMultimodalLM.from_pretrained("utter-project/TowerVideo-2B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -75,12 +75,12 @@ from transformers import AutoProcessor, LlavaOnevisionForConditionalGeneration
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# Load the model in half-precision
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model = LlavaOnevisionForConditionalGeneration.from_pretrained(
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device_map="auto"
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processor = AutoProcessor.from_pretrained(
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"utter-project/TowerVideo-
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# Use your local video
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# Load the model in half-precision
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model = LlavaOnevisionForConditionalGeneration.from_pretrained(
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"utter-project/TowerVideo-2B",
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device_map="auto"
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processor = AutoProcessor.from_pretrained(
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"utter-project/TowerVideo-2B"
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# Use your local video
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