Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
Retrieval
STS
Classification
Clustering
Reranking
vllm
text-embeddings-inference
Instructions to use tencent/KaLM-Embedding-Gemma3-12B-2511 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tencent/KaLM-Embedding-Gemma3-12B-2511 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tencent/KaLM-Embedding-Gemma3-12B-2511") 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] - Notebooks
- Google Colab
- Kaggle
`processor_class: Gemma3Processor` in tokenizer_config.json breaks loading with sentence-transformers 6
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1
#8 opened 2 days ago
by
JuanPabloSokil
SpartQA score error?
1
#7 opened 10 months ago
by
williambarberjr
Rerank
1
#5 opened 12 months ago
by
tunglinwood
Question about prompts
1
#4 opened 12 months ago
by
tomaarsen
New SOTA using the kalm dataset
๐ 5
3
#3 opened about 1 year ago
by
LPN64