Sentence Similarity
sentence-transformers
TensorBoard
ONNX
Safetensors
German
xlm-roberta
information retrieval
education
competency
course
text-embeddings-inference
Instructions to use isy-thl/multilingual-e5-base-course-skill-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use isy-thl/multilingual-e5-base-course-skill-tuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("isy-thl/multilingual-e5-base-course-skill-tuned") 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
- Xet hash:
- 4471d2e6a803bd06b35da142c8049b24976c5dd9e557a1501e7176d96863ef8a
- Size of remote file:
- 5.3 kB
- SHA256:
- 4e373d6e47235067daf82767e56a4c3e635e1e8fcdedb2007985e80406420a8b
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