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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4fb7c35f9f6c4457755a80b5bcb44baf22feb3fc5487339b979077b59f4422b
- Size of remote file:
- 4.92 kB
- SHA256:
- 42d25b30af962dde1997b6a14e5866fc21ade86ec10d15f726dd99bb5e45316f
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