Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Kimty/distilbert-base-uncased-inquiry-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kimty/distilbert-base-uncased-inquiry-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kimty/distilbert-base-uncased-inquiry-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kimty/distilbert-base-uncased-inquiry-classifier") model = AutoModelForSequenceClassification.from_pretrained("Kimty/distilbert-base-uncased-inquiry-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac0f8563aee9bfb7ce647bcfe00f13b7925dbafe09eff24124cd76799bcb5b06
- Size of remote file:
- 5.2 kB
- SHA256:
- b62ab83e4d1e6d716581d3dea7928f575ae46461da67fc64afce92c4fcb25a4b
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