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:
- cbbdaa0b8ce5972d2bf4f3ae404e4c313c93474fef92fa14c58e227d419617cc
- Size of remote file:
- 388 kB
- SHA256:
- 8db3219435795f518dd5d57f10e0affe09ae027ee7dd287e42ffd2858387605e
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