Feature Extraction
sentence-transformers
Safetensors
English
Chinese
qwen2
Retrieval
STS
Classification
Clustering
Reranking
vllm
custom_code
text-embeddings-inference
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", trust_remote_code=True) 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
Download imgs/perf.jpg from KaLM-Embedding/KaLM-embedding-multilingual-mini-instruct-v2.5: direct link, hf CLI and curl.
- Browser
- Download file 460 kB
-
https://huggingface.co/KaLM-Embedding/KaLM-embedding-multilingual-mini-instruct-v2.5/resolve/main/imgs/perf.jpg
- Command line
-
hf download hf://KaLM-Embedding/KaLM-embedding-multilingual-mini-instruct-v2.5/imgs/perf.jpg
-
curl -L -o perf.jpg https://huggingface.co/KaLM-Embedding/KaLM-embedding-multilingual-mini-instruct-v2.5/resolve/main/imgs/perf.jpg
460 kB

- Xet hash:
- 89b46890c7d4fa6876a788ac1d14eac996671ec6e5ab63babc858d5677fe36a1
- Size of remote file:
- 460 kB
- SHA256:
- 63c4a391249648d7567dc84eddc0fd29e6dd011a0cc71219c9b502abf91695f9
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