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:
- 14eaaddb9da35b208809e66e6914c4645b6d03810061ed0ad4e9526b269bfd7f
- Size of remote file:
- 4.16 MB
- SHA256:
- 5ee16f62d06b2de985da8634f50ac6f3e64613df770e0670c66ff705a810c222
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