Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use FCameCode/BERT_model_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FCameCode/BERT_model_new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FCameCode/BERT_model_new")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FCameCode/BERT_model_new") model = AutoModelForSequenceClassification.from_pretrained("FCameCode/BERT_model_new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c5d8187b672c8bb336ae80cdb949f5f286c17a5a3ad27077fc62c7c5842461d
- Size of remote file:
- 438 MB
- SHA256:
- c5de7e9b020b4a2fa9102280d851195c71bb03ca13d2bd05286a4536fe377040
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