Instructions to use hf-internal-testing/tiny-random-MvpForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MvpForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MvpForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MvpForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MvpForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ab0253e5b096138f7fe9e474fce8ee1c71939071d0383c170c79ca22d4a8394
- Size of remote file:
- 120 kB
- SHA256:
- 4c73e86be930e7d97bdef04ff1e4e5e1accaa9e8759a47c09cbdaac88ec7c3ee
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