Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use lengocquangLAB/Appearance-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lengocquangLAB/Appearance-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lengocquangLAB/Appearance-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lengocquangLAB/Appearance-classifier") model = AutoModelForSequenceClassification.from_pretrained("lengocquangLAB/Appearance-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19d71a4c7ca9b974454d1f118a272821c464e60cc05feb7314c84a59db80ece1
- Size of remote file:
- 4.92 kB
- SHA256:
- 6a8f3c19bbee4646b17e8daf6a5bbdc8117b79c0a7f2fb48aed5b5e66dcd45e8
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