Text Classification
Transformers
PyTorch
English
deberta-v2
vision-language
autonomous-driving
text-embeddings-inference
Instructions to use wayveai/Lingo-Judge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wayveai/Lingo-Judge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wayveai/Lingo-Judge")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wayveai/Lingo-Judge") model = AutoModelForSequenceClassification.from_pretrained("wayveai/Lingo-Judge", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b64005e10dddc8979ffab354db5be796f48381b5705ff8b5ff39eb42d5626ab6
- Size of remote file:
- 738 MB
- SHA256:
- f270ce497dd3248dfdd1dc89a89d50349c4c71658c972992ad7fe61bcaa4f899
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