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:
- 7af875feb750dfad24e8521cd86bba32a4af7f59d5c0d5b19fbdcc6594ccc5df
- Size of remote file:
- 4.15 MB
- SHA256:
- b07580a0f5e38a8467930a0a656530d3e69bd434215794a814afabea67aef83d
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