Video-Text-to-Text
Transformers
Safetensors
English
gemma4
image-text-to-text
video-captioning
multimodal
gemma
parakeet
Instructions to use SulphurAI/sulphur-caption with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SulphurAI/sulphur-caption with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("SulphurAI/sulphur-caption") model = AutoModelForMultimodalLM.from_pretrained("SulphurAI/sulphur-caption", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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You're going to need ~70gb vram to run this model. The fp8 variant will require ~38gb.
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## Installation
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You need `ffmpeg`, `ffprobe`, and `unzip` available on `PATH`.
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You're going to need ~70gb vram to run this model. The fp8 variant will require ~38gb.
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Note the fp8 variant is ~1.6x faster than the bf16 variant.
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## Installation
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You need `ffmpeg`, `ffprobe`, and `unzip` available on `PATH`.
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