Instructions to use YaHi/student_deberta_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YaHi/student_deberta_large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YaHi/student_deberta_large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YaHi/student_deberta_large") model = AutoModelForSequenceClassification.from_pretrained("YaHi/student_deberta_large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac96ad8ac9729acdf95d382c3b887be11863370ed593b19310b0683448e7e8c9
- Size of remote file:
- 1.74 GB
- SHA256:
- 08c95d48c1162c36b097765020815a2094521247d9a14df0e7200635637efb56
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