Instructions to use ModelTC/bart-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bart-base-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bart-base-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea9e662313d85c468f4a333e5489d324fafc1913a4f350166f6f695af31914de
- Size of remote file:
- 623 Bytes
- SHA256:
- 95e431f1959e43f1a75113e4685ecf3b966a19950bd5c0d11a3cc24d806f0de9
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