Instructions to use hf-internal-testing/tiny-random-MptModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MptModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MptModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MptModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MptModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81e5bd2d28a46602f04cf01d9a8a64df16177ba560381f297a82fd7bc6551468
- Size of remote file:
- 388 kB
- SHA256:
- 90a13ef4365a65dbbe1d0f5f6acaec962645d4c4a96bd1c184c6b386d3223f19
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