Instructions to use YakovElm/Jira_5_RoBERTa_Over_Sampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Jira_5_RoBERTa_Over_Sampling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Jira_5_RoBERTa_Over_Sampling")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Jira_5_RoBERTa_Over_Sampling") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Jira_5_RoBERTa_Over_Sampling") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d28f9094e0da26af40d6d6540bca4bc422b07609d6c589329f6b771a6603d0c9
- Size of remote file:
- 499 MB
- SHA256:
- 94d37d423e9bc712f99c008c6af641728ec2587ed6ebe0f0d64874c0c0f4ce54
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