Instructions to use hf-tiny-model-private/tiny-random-M2M100Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-M2M100Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-M2M100Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-M2M100Model") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-M2M100Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82f3b616b63f0a0ae41dc7370ae383bb3b69ce607022ec381616b6a2d89a608c
- Size of remote file:
- 8.24 MB
- SHA256:
- 99dce1851d64e4926f6aea65281612e28c0fbeb716eecf52a2aedf45e294c537
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