Instructions to use hf-internal-testing/tiny-random-MistralModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MistralModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MistralModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MistralModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MistralModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dead594dbfd7fab18440b7178d9b626c47af7c55c0cf8804f94b945ebdee53cd
- Size of remote file:
- 4.27 MB
- SHA256:
- a6e5df2d119b958399185bd9136844a65919a0218adb7fb73b8a9e369510bb94
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