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:
- ef47ed47e48610a31eb43dea78c4c877c515896a7cd98daf14da2f32c531c9fb
- Size of remote file:
- 438 MB
- SHA256:
- ab405f71617713bcf3a5c94cb9d5f87bf239befac23c70259a8f072aa76c449e
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