Instructions to use m42-health/CXformer-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m42-health/CXformer-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="m42-health/CXformer-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("m42-health/CXformer-base") model = AutoModel.from_pretrained("m42-health/CXformer-base") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- f114c9fc041f66c4f7c79588cbd7f95b6e84934fee8a908abad3ba7c70e415df
- Size of remote file:
- 576 kB
- SHA256:
- b6e946b4365f02a9cafcc2d04808badab01878680e2625de6c573f10168c7c2f
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