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:
# pip install -U transformers accelerate # 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 requirements.txt
Browse files- requirements.txt +6 -6
requirements.txt
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@@ -5,14 +5,14 @@
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accelerate==1.14.0
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av==17.1.0
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librosa==0.11.0
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numpy==2.
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opencv-python-headless
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safetensors==0.8.0
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scipy==1.18.0
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soundfile==0.14.0
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torch==2.
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torchcodec==0.14.0
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torchvision==0.
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transformers==5.
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-e ./vllm
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accelerate==1.14.0
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av==17.1.0
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librosa==0.11.0
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numpy==2.3.5
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| 9 |
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opencv-python-headless==5.0.0.93
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| 10 |
safetensors==0.8.0
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| 11 |
scipy==1.18.0
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| 12 |
soundfile==0.14.0
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| 13 |
+
torch==2.11.0
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torchcodec==0.14.0
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torchvision==0.26.0
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transformers==5.13.0
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-e ./vllm
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