Video-Text-to-Text
Transformers
Safetensors
English
Chinese
qwen2_5_vl
image-text-to-text
video-understanding
multimodal
SWIM
Qwen2.5-VL
fine-grained-understanding
Eval Results (legacy)
text-generation-inference
Instructions to use BBBBCHAN/SWIM-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BBBBCHAN/SWIM-7B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("BBBBCHAN/SWIM-7B") model = AutoModelForImageTextToText.from_pretrained("BBBBCHAN/SWIM-7B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7030cf2e58dead38199a68a8cd6f6f1a609a6072d7fb38ba5f85b3bb7e21557
- Size of remote file:
- 11.4 MB
- SHA256:
- 9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
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