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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 389afafc2a72450041975cf92a4332f33b8710712dc797dd955171ce7bb706cf
- Size of remote file:
- 3.26 MB
- SHA256:
- 62252b4ba32d4bc9ca7ca04a7e9a5c8f234f0d7b19742cc1d55e30cdbe23b63a
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