Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use RaspberryVitriol/polar4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RaspberryVitriol/polar4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RaspberryVitriol/polar4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RaspberryVitriol/polar4") model = AutoModelForSequenceClassification.from_pretrained("RaspberryVitriol/polar4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2aa2ea6926c7d351c18c9abdb57cd350166fad97da8a49ab5430a8cfd19edc73
- Size of remote file:
- 5.84 kB
- SHA256:
- 44190a9088e75603daabec7b1a635da56e9265af491bd39fb5770066d2407068
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