Instructions to use MMInstruction/YingVLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMInstruction/YingVLM with Transformers:
# Load model directly from transformers import AutoProcessor, VLM processor = AutoProcessor.from_pretrained("MMInstruction/YingVLM") model = VLM.from_pretrained("MMInstruction/YingVLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 487d225ce1c86bc58c4582b2c807fd5d94664c2ea9f5064cc40a637b28226a6b
- Size of remote file:
- 589 kB
- SHA256:
- 6fd7e445833dd0889206aba242c2a51ecbae2437fd328d1759a35475fd8c0423
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