Instructions to use xshubhamx/bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/bart-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/bart-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/bart-base") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/bart-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6498839baea37c1d71d53e496d7b99e8f293411b8066b6c906e21f29093a4d5
- Size of remote file:
- 1.12 GB
- SHA256:
- 7086c5d816dc21242b798a49334f2be4a5914e976bf8a4dca4e56dba0d19f9a6
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