Instructions to use ModelTC/bart-base-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bart-base-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-sst2") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bart-base-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c76cd3db592f4f04cc57357b42c4a5d87e4fc04c12c18b89e5be97f32b30f281
- Size of remote file:
- 623 Bytes
- SHA256:
- 747ae5ba86616b53feff7e5521a7aa379393eb27a5054827d5d5dfa6e81d75a2
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