Instructions to use HIT-TMG/JevEmbed-Qwen3-Embedding-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HIT-TMG/JevEmbed-Qwen3-Embedding-4B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HIT-TMG/JevEmbed-Qwen3-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] - Notebooks
- Google Colab
- Kaggle
File size: 59 Bytes
a96ec65 | 1 2 3 4 5 | {
"max_seq_length": 1024,
"do_lower_case": false
}
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