Instructions to use hf-internal-testing/tiny-random-MistralForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MistralForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MistralForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MistralForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MistralForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f49c585ef58e25ccaf74a165b7eb6c9a3b28769f0e1f96a55cbb7787f9dee648
- Size of remote file:
- 4.15 MB
- SHA256:
- a5e4ade1ed14e86f7733be4e7000b044861c8dbb59e0431644e4367d0630a7ef
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