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:
- 9b7356b764ac499685b87ff7a111de4c929ae7e5874e30544f5ba711b6191e25
- Size of remote file:
- 5.78 kB
- SHA256:
- 4410e061e9e9063477d5b57f26eeda29d8b119aba156a0a7c510c00764b1fd9b
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