Instructions to use hf-internal-testing/tiny-random-XmodForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XmodForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-XmodForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XmodForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-XmodForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe8fa5d09c95bf93c7f9140002c5b6852dd157970c94627d6d22f241de750740
- Size of remote file:
- 32.2 MB
- SHA256:
- 8f0ea198582e79d6cccfd0c2d7bd29cba934398a53e48141e092e19dac0323c2
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