Instructions to use hf-internal-testing/tiny-random-EuroBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-EuroBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-EuroBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-EuroBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-EuroBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f08f8da5a447decd58e7d6aa09e49b12fa1be373f37d47da9d0908715273e6c
- Size of remote file:
- 17.2 MB
- SHA256:
- 98d4a1d32152d6cedf85b5e88f3b205106dca1fe72aaab34e0ac13c238421069
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