Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use daveni/aesthetic_attribute_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daveni/aesthetic_attribute_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="daveni/aesthetic_attribute_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("daveni/aesthetic_attribute_classifier") model = AutoModelForSequenceClassification.from_pretrained("daveni/aesthetic_attribute_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6454c68f85b78c7d178897d01171437d0f21a83a9a9c8e1a3939893f77de054f
- Size of remote file:
- 3.06 kB
- SHA256:
- 7ff6b8c3ec1de9376464e225a0c71ed511500ebefa17b3d69f9444d73a5ba34b
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