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:
- b6b1d16a0114303f4b8f3adb62128d1395ab925a6a1791a33878b20f3554c2fe
- Size of remote file:
- 178 kB
- SHA256:
- e52bc4a42b3ef67673aab9b8056dc5d4bf1794e4f6a037459be4f57042f0b2f4
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