Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Zaid/bert-fine-tuned-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zaid/bert-fine-tuned-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Zaid/bert-fine-tuned-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Zaid/bert-fine-tuned-cola") model = AutoModelForSequenceClassification.from_pretrained("Zaid/bert-fine-tuned-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4225961ac2ae76d091f018c5a7c1ea0ee35dd3c39fafc34a633f79fe363e164c
- Size of remote file:
- 433 MB
- SHA256:
- 15c007bc74a84349e7000a2f087cf39238adde43bf6d24df94b7c41611de56f8
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