Sentence Similarity
sentence-transformers
Safetensors
qwen2
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
type mismatch
pinned 5
#6 opened over 1 year ago
by
michaelfeil
convert to GGUF format?
17
#8 opened over 1 year ago
by
kalle07
This model literally beats all the other models in the needle in the haystack challenge
👍 3
3
#7 opened over 1 year ago
by
LPN64
KaLM-embedding-multilingual-max-v1
4
#5 opened over 1 year ago
by
gururaser