Instructions to use YagiASAFAS/MsIssuesBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YagiASAFAS/MsIssuesBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YagiASAFAS/MsIssuesBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YagiASAFAS/MsIssuesBERT") model = AutoModelForSequenceClassification.from_pretrained("YagiASAFAS/MsIssuesBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 873ef59a2b3130962681ec7f9828e2774055064cfca6106cf4dd12a049340233
- Size of remote file:
- 438 MB
- SHA256:
- 6987c19b6566dd868d1ca676420c686888c38f155c2654a81f9194f15d3fa892
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