Instructions to use unum-cloud/uform3-image-text-multilingual-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unum-cloud/uform3-image-text-multilingual-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="unum-cloud/uform3-image-text-multilingual-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unum-cloud/uform3-image-text-multilingual-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download text_encoder.mlpackage/Data/com.apple.CoreML/model.mlmodel from unum-cloud/uform3-image-text-multilingual-base: direct link, hf CLI and curl.
- Browser
- Download file 74.1 kB
-
https://huggingface.co/unum-cloud/uform3-image-text-multilingual-base/resolve/main/text_encoder.mlpackage/Data/com.apple.CoreML/model.mlmodel
- Command line
-
hf download hf://unum-cloud/uform3-image-text-multilingual-base/text_encoder.mlpackage/Data/com.apple.CoreML/model.mlmodel
-
curl -L -o model.mlmodel https://huggingface.co/unum-cloud/uform3-image-text-multilingual-base/resolve/main/text_encoder.mlpackage/Data/com.apple.CoreML/model.mlmodel
74.1 kB
- Xet hash:
- d83908952457f989817cd3163b23015241b25bbe901e9edfc5332e6a890d072a
- Size of remote file:
- 74.1 kB
- SHA256:
- b388380d8fdcd0271c9b851c22348453c36463cf43aa3d656b7fa9aa6ea52c42
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