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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89802b578f4fc517d834e4b77012896e068d9a7fec9082708b8bc11b0ac04cb9
- Size of remote file:
- 178 kB
- SHA256:
- 60349ae89bb817fd2e47d96c69e5de7950eed3e8478ae6053318db0c632485ff
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