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.pt from unum-cloud/uform3-image-text-multilingual-base: direct link, hf CLI and curl.
- Browser
- Download file 240 MB
-
https://huggingface.co/unum-cloud/uform3-image-text-multilingual-base/resolve/main/text_encoder.pt
- Command line
-
hf download hf://unum-cloud/uform3-image-text-multilingual-base/text_encoder.pt
-
curl -L -o text_encoder.pt https://huggingface.co/unum-cloud/uform3-image-text-multilingual-base/resolve/main/text_encoder.pt
240 MB
- Xet hash:
- a9afeaa0019f7869aefb3e71c05611b957c95adf2dc8d9dc9d7eafa9f996fa50
- Size of remote file:
- 240 MB
- SHA256:
- 373485cd65cc62c3e41bf623b75171981fe1160e13f84d5f05499e8e2c34e63f
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