Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use devinitorg/cdp-multi-classifier-sub-classes-weighted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devinitorg/cdp-multi-classifier-sub-classes-weighted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="devinitorg/cdp-multi-classifier-sub-classes-weighted")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("devinitorg/cdp-multi-classifier-sub-classes-weighted") model = AutoModelForSequenceClassification.from_pretrained("devinitorg/cdp-multi-classifier-sub-classes-weighted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aff785a9677538e7a04f2cd823e66e09304e3eb366fc9413d6b87d03f08b7a2c
- Size of remote file:
- 673 MB
- SHA256:
- 83c262436936c71f4004772459c0711108ac53aafe99a5ac32774ab5f20f3cdc
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