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:
- 0d3c03e95abb4a2ab0694a7b39b5cdb10c4a69a45fe0696d41ff4f0189ac032f
- Size of remote file:
- 4.15 MB
- SHA256:
- a0a9eb50acdb06378247eab400e25d14cbc0554f6179961989f4b6272c2dd742
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