Video-Text-to-Text
Transformers
Safetensors
qwen2_5_omni
text-to-audio
multimodal
video-captioning
audio-visual
ugc
Instructions to use Memories-ai/UGC-VideoCaptioner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Memories-ai/UGC-VideoCaptioner with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Memories-ai/UGC-VideoCaptioner") model = AutoModelForMultimodalLM.from_pretrained("Memories-ai/UGC-VideoCaptioner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Memories-ai/UGC-VideoCaptioner: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Memories-ai/UGC-VideoCaptioner/resolve/main/tokenizer.json
- Command line
-
hf download hf://Memories-ai/UGC-VideoCaptioner/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Memories-ai/UGC-VideoCaptioner/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- c38861918c23af9030c7cfd8daefca315dc8e0fde29740104d391c2360e69753
- Size of remote file:
- 11.4 MB
- SHA256:
- 8441917e39ae0244e06d704b95b3124795cec478e297f9afac39ba670d7e9d99
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