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:
- da3b01aa87038c152abc326637bb23b040c77a6902773b2447d871336535017c
- Size of remote file:
- 3.28 MB
- SHA256:
- 71aba0eacd1ddb038be7faa1bf4dca0388d64ffce38ee5125d1c4b4c5c860a0d
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