Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use jakka/Bert_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jakka/Bert_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jakka/Bert_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jakka/Bert_Classifier") model = AutoModelForSequenceClassification.from_pretrained("jakka/Bert_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ede1954f75dc3dd23934ec12fc73fe910a50533e595fadd8edb3b46fef1e5c4c
- Size of remote file:
- 433 MB
- SHA256:
- 8c4ebb4f4b361017de72025bb6145936a6e835898cedcc5621f05b95d766cc87
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