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:
- 63085d65997e6ce3aa6dd668a7000c3e5c252d7661462ffa8206d4c73fd747e9
- Size of remote file:
- 1.12 GB
- SHA256:
- de2af65575d32d4276437d70b46c33bab7af53a9b5a7d9a3f1dc5cf3b67ac3b7
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