Sentence Similarity
sentence-transformers
Safetensors
PEFT
Korean
qwen3
feature-extraction
text-embedding
information-retrieval
korean
finance
lora
text-embeddings-inference
Instructions to use BCCard/MoAI-Embedding-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BCCard/MoAI-Embedding-4B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BCCard/MoAI-Embedding-4B") 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] - PEFT
How to use BCCard/MoAI-Embedding-4B with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
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