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:
- 7e952511378f3fe7de2e6fce8ab63af81e92faaa819d2c49f90e775ce888a19c
- Size of remote file:
- 4.15 MB
- SHA256:
- 39b8cc65fd908d91eed31f4f41c02d521f5c58690eaedf92dc671e856b0faaf0
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