Instructions to use hf-tiny-model-private/tiny-random-PLBartForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-PLBartForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-PLBartForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-PLBartForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-PLBartForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7abfaac3f6838c511d5d57b266e4e7bd0a5909791734448c0428a932040f83f4
- Size of remote file:
- 3.26 MB
- SHA256:
- 25c0c4daede6ec57987889dc367066759cb2f7c3c1c5ac1ce684081d622f36b6
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