Video-Text-to-Text
Transformers
Safetensors
qwen2_5_omni
text-to-audio
multimodal
video-captioning
audio-visual
ugc
Instructions to use openinterx/UGC-VideoCaptioner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openinterx/UGC-VideoCaptioner with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("openinterx/UGC-VideoCaptioner") model = AutoModelForMultimodalLM.from_pretrained("openinterx/UGC-VideoCaptioner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from openinterx/UGC-VideoCaptioner: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/openinterx/UGC-VideoCaptioner/resolve/main/tokenizer.json
- Command line
-
hf download hf://openinterx/UGC-VideoCaptioner/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/openinterx/UGC-VideoCaptioner/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- f59fce72f616172554e519584834dd7b49bdc28f94a018b533f17d49de8d78d1
- Size of remote file:
- 11.4 MB
- SHA256:
- 8441917e39ae0244e06d704b95b3124795cec478e297f9afac39ba670d7e9d99
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