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:
- 11375a9f14797422bdd0871e538c27c8045331582cfb6dda9337acd3a9425ed4
- Size of remote file:
- 178 kB
- SHA256:
- a8e81c01ab5a383f299309d9364cc94216c15ea58d2576eac59747497389c9c4
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