Sentence Similarity
sentence-transformers
Safetensors
Luxembourgish
new
dataset_size:120000
multilingual
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use impresso-project/histlux_ocr_error_denoising_lrec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use impresso-project/histlux_ocr_error_denoising_lrec with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("impresso-project/histlux_ocr_error_denoising_lrec", trust_remote_code=True) sentences = [ "Who is filming along?", "Wién filmt mat?", "Weider huet den Tatarescu drop higewisen, datt Rumänien durch seng krichsbedélegong op de 6eite vun den allie'erten 110.000 mann verluer hätt.", "Brambilla 130.08.03 St." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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