Video-Text-to-Text
Transformers
Safetensors
internvl
image-text-to-text
video
dense-video-captioning
temporal-grounding
highlight-detection
video-reasoning
Instructions to use andaba/TEMPURA-InternVL3-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andaba/TEMPURA-InternVL3-2B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("andaba/TEMPURA-InternVL3-2B") model = AutoModelForMultimodalLM.from_pretrained("andaba/TEMPURA-InternVL3-2B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from andaba/TEMPURA-InternVL3-2B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/andaba/TEMPURA-InternVL3-2B/resolve/main/tokenizer.json
- Command line
-
hf download hf://andaba/TEMPURA-InternVL3-2B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/andaba/TEMPURA-InternVL3-2B/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- e9863e654881b0048fa872ccd198fae96e8554875a549e79d5054ff4c85ddeb4
- Size of remote file:
- 11.4 MB
- SHA256:
- fd0c8be238c81a5f0450067d9565e16794aef2699df631fcf3dd0c2ac4842b06
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