Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use Twoone21/bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Twoone21/bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Twoone21/bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Twoone21/bert_model") model = AutoModelForSequenceClassification.from_pretrained("Twoone21/bert_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d20b52c0ed7931673018384f4a869ef764ad0f78b088ea36d2d1396f99748666
- Size of remote file:
- 436 MB
- SHA256:
- 41abe76eac329f5b629219ca621b0c486729f059ba1e02ddd04ade9839f23313
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