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:
- 56d9996145fbdd0eaf2f1d153cc4c6c589e1317010f217ad105bf2163cde0ef7
- Size of remote file:
- 1.47 kB
- SHA256:
- 4df0723e25396adc59bb9added161c2980b9b62ceb5827a0e48943b97cb4fd5b
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