Instructions to use hf-internal-testing/tiny-random-M2M100ForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-M2M100ForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-M2M100ForConditionalGeneration") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-M2M100ForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62f812f8fa34028c1c0f1f26b7fe48bbd61cd446e66e97e9b62ecfcd3ed3d7e4
- Size of remote file:
- 8.26 MB
- SHA256:
- ae0c5943b0a2b1048cd5ff14d9278ec7c8d451f635dfd8d0fdd95d05edcab560
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