Instructions to use hf-internal-testing/tiny-random-MraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MraModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MraModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MraModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d268f7c36d8a50c0b7331e74d6f769004165b7d35446aa931c4a68b0ae4e91e
- Size of remote file:
- 178 kB
- SHA256:
- ff64694b05fd4d0c3f65bc566b0bbe12ebf5e272149a58181ab96c281bc7e21d
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