Instructions to use hf-internal-testing/tiny-random-VisionTextDualEncoderModel-vit-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VisionTextDualEncoderModel-vit-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-VisionTextDualEncoderModel-vit-bert")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-VisionTextDualEncoderModel-vit-bert") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-VisionTextDualEncoderModel-vit-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 497044c2e328eba380d223712506e7397188cd693aba2c6915e6f9e236043c4d
- Size of remote file:
- 717 kB
- SHA256:
- a33606b9968a9357721da3f76a9dccc040560850e74da3726d144ad6fcbb2efd
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