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:
- 1df8d95de50669f19a2f0522b7f5aa831202e4cb96566ceb5b377c5784a8d1ed
- Size of remote file:
- 2.42 MB
- SHA256:
- d8f7c76ed2a5e0822be39f0a4f95a55eb19c78f4593ce609e2edbc2aea4d380a
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