Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use RaspberryVitriol/polar3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RaspberryVitriol/polar3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RaspberryVitriol/polar3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RaspberryVitriol/polar3") model = AutoModelForSequenceClassification.from_pretrained("RaspberryVitriol/polar3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f0ca7ab19f49df2890586c68c33694000b4ae6cf1097253793f17f25d73920c
- Size of remote file:
- 5.84 kB
- SHA256:
- 87b20cd2e865084d219110f1b12e30b6a5906ced72460aa7a602f0ea91197b5a
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