Feature Extraction
sentence-transformers
Safetensors
English
fusion-embedding-connector
embeddings
multimodal
audio
retrieval
matryoshka
qwen3-vl
adapters
custom_code
Instructions to use EximiusLabs/fusion-embedding-2-2b-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use EximiusLabs/fusion-embedding-2-2b-preview with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("EximiusLabs/fusion-embedding-2-2b-preview", 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
| { | |
| "model_type": "SentenceTransformer", | |
| "__version__": { | |
| "sentence_transformers": "5.7.0", | |
| "transformers": "5.14.1", | |
| "pytorch": "2.13.0" | |
| }, | |
| "prompts": { | |
| "query": "Retrieve images or text relevant to the user's query.", | |
| "document": "Represent the user's input." | |
| }, | |
| "default_prompt_name": "query", | |
| "similarity_fn_name": "cosine" | |
| } | |