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:
- 7b9f684d82b96887f5b7bb26cd23b99959519e262e4ed69ec1017ef350eb2123
- Size of remote file:
- 436 MB
- SHA256:
- a96e98aed476fa45aebc2f32ac84f6420cf798a6456bb67a237a6240f2f6258c
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