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:
- 1777cb0ba9ea54e7d0c347932ed92c9a875cefb60a89ae9ec10ad95486abf477
- Size of remote file:
- 8.26 MB
- SHA256:
- 1d5caf21835eac34189e020f3603917bce34a853d54311d2c42df2ef6180034a
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