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, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-VisionTextDualEncoderModel-vit-bert") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-VisionTextDualEncoderModel-vit-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ca440f505cd57622c3173615685f5951652250eb459c3ad65258d4ddf584df6
- Size of remote file:
- 717 kB
- SHA256:
- 5e0a5cfffb88244285bcf7a7ebb0c8f0235eb8917c40770ccfef2b7c4eb064ec
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