Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use seeeeun27/bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seeeeun27/bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="seeeeun27/bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("seeeeun27/bert_model") model = AutoModelForSequenceClassification.from_pretrained("seeeeun27/bert_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b686b03d926503f14e23753c9c92340a558f49aa986146522d2fde5311da8d6
- Size of remote file:
- 5.3 kB
- SHA256:
- 8dfa11898e48257c5d42e96fc3433dfb7f0d3aec940aec09cc447ed370f54ee4
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