Instructions to use hf-internal-testing/tiny-random-PLBartForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PLBartForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-PLBartForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PLBartForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-PLBartForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bbab55d8f6af7ba51f2aa9f3e0b64de4f52c26c13aaf9062c5e82c1f398358b
- Size of remote file:
- 3.28 MB
- SHA256:
- b812913967dc78e13d7445a0b922bcac0b6376d5f59af00fc6425c25b6c814df
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