Text Classification
setfit
Safetensors
sentence-transformers
German
distilbert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use mbley/german-webtext-quality-classifier-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use mbley/german-webtext-quality-classifier-base with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("mbley/german-webtext-quality-classifier-base") - sentence-transformers
How to use mbley/german-webtext-quality-classifier-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mbley/german-webtext-quality-classifier-base") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
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README.md
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preds = model("在 Greding 出 口 离 开 A9 高 速 公 路 。")
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## Training Details
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### Training Hyperparameters
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preds = model("在 Greding 出 口 离 开 A9 高 速 公 路 。")
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## Training Details
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### Training Hyperparameters
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