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:
- a0b0f790ac32ab90f88d92858d1d37d72c2be16fb6d9ec5dec4512d5d2a81b76
- Size of remote file:
- 3.58 kB
- SHA256:
- ba28ec9e1b9102d89d39c2d00f142835e5237a230517b28f355b428c359af971
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