Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use dynncat/bert_model_result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dynncat/bert_model_result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dynncat/bert_model_result")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dynncat/bert_model_result") model = AutoModelForSequenceClassification.from_pretrained("dynncat/bert_model_result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
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