Instructions to use KRAFTON/Raon-VisionEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KRAFTON/Raon-VisionEncoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="KRAFTON/Raon-VisionEncoder", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KRAFTON/Raon-VisionEncoder", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df1a9618a768e712b38f6f65cdb316c522042d314dd78ec506be33be1acd1578
- Size of remote file:
- 4.54 GB
- SHA256:
- fdc6f253e8535fed9d8f93c18ed0c701bef9e3329f35dc62d778d7a404da812a
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