Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use baikkkanu/bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baikkkanu/bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="baikkkanu/bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("baikkkanu/bert_model") model = AutoModelForSequenceClassification.from_pretrained("baikkkanu/bert_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 011339ece7c531fc4db07cad342f28b4a1fde663e81ea8ee7112c57d30864266
- Size of remote file:
- 5.3 kB
- SHA256:
- a2e88ce09e020edc2a56b336e81ed0d533bf4a7990394db25539143b7c16a590
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