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:
- c48ab6188de5348d67b9c2cc0749563765d55ebc422f322618841d36b2b8e177
- Size of remote file:
- 16.8 MB
- SHA256:
- f5a5d9ac608d4c9863f808e650d608d3e622a38afec672554356ebf8dcf7e860
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