Instructions to use hf-internal-testing/tiny-random-M2M100Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-M2M100Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-M2M100Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-M2M100Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-M2M100Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb948ffddadefebdbc67305b352115cd9dd821e8ef6f24c53d3cd18c5ca529ae
- Size of remote file:
- 8.31 MB
- SHA256:
- f2fcba51eb13e07a91b91b96111bf887c0048ca58f8032639a9e9032ec5d1176
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