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:
- 69a3d2d86507d9b27c10455d5f2bf2b3bb599cc56951cb108a008d84cc7037a1
- Size of remote file:
- 4.15 MB
- SHA256:
- 2db2a062e1e81493143f3da8e5e3a53b0deeead3127670290b6fb3ec1e8f288c
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