Video-Text-to-Text
Transformers
Safetensors
English
gemma4
image-text-to-text
video-captioning
multimodal
gemma
parakeet
Instructions to use vdaular/sulphur-caption with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vdaular/sulphur-caption with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("vdaular/sulphur-caption") model = AutoModelForMultimodalLM.from_pretrained("vdaular/sulphur-caption", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download parakeet/tokenizer.json from vdaular/sulphur-caption: direct link, hf CLI and curl.
- Browser
- Download file 1.16 MB
-
https://huggingface.co/vdaular/sulphur-caption/resolve/main/parakeet/tokenizer.json
- Command line
-
hf download hf://vdaular/sulphur-caption/parakeet/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/vdaular/sulphur-caption/resolve/main/parakeet/tokenizer.json
1.16 MB
File too large to display, you can check the raw version instead.