Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use lengocquangLAB/Palate-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lengocquangLAB/Palate-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lengocquangLAB/Palate-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lengocquangLAB/Palate-classifier") model = AutoModelForSequenceClassification.from_pretrained("lengocquangLAB/Palate-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54c0a6664228d61031c407e51980abdc5b2dcf4ebdc7497e3c23baa59e2ad4d0
- Size of remote file:
- 4.92 kB
- SHA256:
- b977a8a1bc1790b10b3b89d1a3d2a9197ccbfc22b03e3165ebf354e157ee9246
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