Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use FCameCode/BERT_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FCameCode/BERT_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FCameCode/BERT_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FCameCode/BERT_model") model = AutoModelForSequenceClassification.from_pretrained("FCameCode/BERT_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c272a4e749837ff7d6016c8b7fd21110731b38ce5e4deee0db8becead4dabf98
- Size of remote file:
- 438 MB
- SHA256:
- 18c3b1971fdc309eb06f2a684f7fa163d6895e195633eb758671d6c3223464d5
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