Text Classification
Transformers
PyTorch
TensorFlow
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Ramuvannela/bert-fine-tuned-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ramuvannela/bert-fine-tuned-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ramuvannela/bert-fine-tuned-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ramuvannela/bert-fine-tuned-cola") model = AutoModelForSequenceClassification.from_pretrained("Ramuvannela/bert-fine-tuned-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c68d23574fdb176d4bcbebc39fef7478b901a004e9aa191afe6b03e584b9885
- Size of remote file:
- 433 MB
- SHA256:
- bba352120a6c0ddf9e7da6576ebd149de10101da3b2fdb7d81e0df69c82629c5
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