Instructions to use hf-internal-testing/tiny-random-DistilBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DistilBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-DistilBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DistilBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-DistilBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f33a474ded7faefdc1f8d7076b491f6fe2179edcc248f0d53bff9df1d80da40e
- Size of remote file:
- 360 kB
- SHA256:
- fb29da1db70b40db11e7e4d4fdacda741860005d7521a807a90d833d56218ce2
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