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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f13f83fd7b6fb6af45c1b4ff9a1cfc804e8ae5c1bec449add1c803a94cba2c4
- Size of remote file:
- 4.16 MB
- SHA256:
- 22c2784352e256181e77975ec4462a031e4bd338af158032b56a18eb5bd10fb3
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