Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_label
Generated from Trainer
text-embeddings-inference
Instructions to use TaeGee/bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TaeGee/bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TaeGee/bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TaeGee/bert_model") model = AutoModelForSequenceClassification.from_pretrained("TaeGee/bert_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 275b784ae00200183cc2e08618d28261fd2eff1d5e3faf89c9a499c8f5baaf55
- Size of remote file:
- 5.3 kB
- SHA256:
- e6df4271f6a3143150f3237bfac2089b5634185eef2dab8cbfc881114b9ed320
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