Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use kyungmin011029/code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kyungmin011029/code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kyungmin011029/code")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kyungmin011029/code") model = AutoModelForSequenceClassification.from_pretrained("kyungmin011029/code", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7aad1040f2d07a38afc80db4c1d54aa32491fc1fe7e3162421fe57fbd429ccc
- Size of remote file:
- 443 MB
- SHA256:
- 553ed73d3ce696b80c0a0ab82efbbbcad4d1f8c8621cd62208d8a5911ae0a057
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