Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Arielkanevsky/Complaints_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arielkanevsky/Complaints_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Arielkanevsky/Complaints_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arielkanevsky/Complaints_Classifier") model = AutoModelForSequenceClassification.from_pretrained("Arielkanevsky/Complaints_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a0bed08480da6676695865ff47915c3d40c3a59a924aead2dffbb123611cc2b
- Size of remote file:
- 3.58 kB
- SHA256:
- 00df78fde842c04ad1acd62aee88a17e64ab4c29d0b3db730a7b3337ad781b5f
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