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:
- fa07536fc3665fb9b427d3de216138266a63029462bf3028c6d25f5d6581ec84
- Size of remote file:
- 4.15 MB
- SHA256:
- b831c30e5328ec50ca5f3000010410c1519703cf1248080e89f02352e69e9ce9
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