Feature Extraction
sentence-transformers
Safetensors
English
Chinese
Retrieval
STS
Classification
Clustering
Reranking
vllm
Instructions to use KaLM-Embedding/KaLM-embedding-multilingual-mini-instruct-v2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use KaLM-Embedding/KaLM-embedding-multilingual-mini-instruct-v2.5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KaLM-Embedding/KaLM-embedding-multilingual-mini-instruct-v2.5") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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base_model:
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- Qwen/Qwen2.5-0.5B
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- HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v2
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pipeline_tag:
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library_name: sentence-transformers
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tags:
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- Retrieval
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base_model:
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- Qwen/Qwen2.5-0.5B
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- HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v2
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pipeline_tag: feature-extraction
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library_name: sentence-transformers
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tags:
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- Retrieval
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