Text Classification
Transformers
PyTorch
TensorBoard
bert
classification
Generated from Trainer
text-embeddings-inference
Instructions to use cedomin/Task1a_class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cedomin/Task1a_class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cedomin/Task1a_class")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cedomin/Task1a_class") model = AutoModelForSequenceClassification.from_pretrained("cedomin/Task1a_class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c0ae77992d717893a3b823c6f6f7df780748780991eab63bf83df844e6cc7bf
- Size of remote file:
- 438 MB
- SHA256:
- 1db8304601764cce6919e3461e7d752deb459fe77e7a1e8974d04f7eab87c736
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