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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7785dd4cbec7b422b88b8066004c3f4d47f3e9e91c7148add5c4112a08c756d
- Size of remote file:
- 3.58 kB
- SHA256:
- 60956c8935bba7942f2b5f32fe7b97cd3ca5073cd91b7c28edcb5d63a9bf6ae9
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