Sentence Similarity
sentence-transformers
Safetensors
apertus
embeddings
retrieval
multilingual
swiss
apertus-1.1
bidirectional
matryoshka
Mixture of Experts
language-moe
sparse-routing
Instructions to use andreasmartin/apertus-v1.1-swiss-embed-0.4b-bidir-langmoe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use andreasmartin/apertus-v1.1-swiss-embed-0.4b-bidir-langmoe with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("andreasmartin/apertus-v1.1-swiss-embed-0.4b-bidir-langmoe") sentences = [ "Das ist eine glückliche Person", "Das ist ein glücklicher Hund", "Das ist eine sehr glückliche Person", "Heute ist ein sonniger Tag" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "expert_names": [ | |
| "de", | |
| "en", | |
| "fr", | |
| "it", | |
| "rm", | |
| "gsw", | |
| "shared" | |
| ], | |
| "top_k": 2, | |
| "shared_expert_topk_selections": 0, | |
| "by_role_and_declared_language": { | |
| "document:de": { | |
| "top1:en": 4, | |
| "top2:de": 49, | |
| "top1:de": 96, | |
| "top2:en": 25, | |
| "top2:fr": 65, | |
| "top1:it": 38, | |
| "top2:gsw": 11, | |
| "top1:fr": 38, | |
| "top2:it": 26, | |
| "n": 176, | |
| "mean_router_entropy": 1.685270244318182 | |
| }, | |
| "document:en": { | |
| "top1:en": 27, | |
| "top2:de": 59, | |
| "top1:de": 50, | |
| "top2:fr": 31, | |
| "top1:fr": 46, | |
| "top2:it": 13, | |
| "top2:en": 30, | |
| "top1:it": 10, | |
| "n": 133, | |
| "mean_router_entropy": 1.705111112781955 | |
| }, | |
| "document:fr": { | |
| "top1:en": 7, | |
| "top2:fr": 64, | |
| "top1:it": 45, | |
| "top2:de": 52, | |
| "top1:de": 27, | |
| "top2:it": 56, | |
| "top1:fr": 100, | |
| "top2:en": 7, | |
| "n": 179, | |
| "mean_router_entropy": 1.6696601396648045 | |
| }, | |
| "document:gsw": { | |
| "top1:de": 71, | |
| "top2:fr": 28, | |
| "top2:gsw": 38, | |
| "top1:fr": 8, | |
| "top2:de": 8, | |
| "top2:it": 2, | |
| "top2:rm": 1, | |
| "top1:it": 1, | |
| "top2:en": 3, | |
| "n": 80, | |
| "mean_router_entropy": 1.6836649625 | |
| }, | |
| "document:it": { | |
| "top1:it": 127, | |
| "top2:de": 37, | |
| "top2:en": 13, | |
| "top2:fr": 109, | |
| "top1:de": 25, | |
| "top2:it": 19, | |
| "top1:fr": 23, | |
| "top1:en": 4, | |
| "top2:rm": 1, | |
| "n": 179, | |
| "mean_router_entropy": 1.6558301787709497 | |
| }, | |
| "document:rm": { | |
| "top1:it": 78, | |
| "top2:de": 21, | |
| "top1:de": 39, | |
| "top2:fr": 61, | |
| "top1:fr": 19, | |
| "top2:it": 21, | |
| "top2:rm": 32, | |
| "top1:rm": 4, | |
| "top2:gsw": 3, | |
| "top2:en": 3, | |
| "top1:en": 1, | |
| "n": 141, | |
| "mean_router_entropy": 1.716398134751773 | |
| }, | |
| "query:de": { | |
| "top1:en": 4, | |
| "top2:de": 59, | |
| "top1:de": 108, | |
| "top2:en": 31, | |
| "top2:gsw": 22, | |
| "top2:fr": 46, | |
| "top1:it": 26, | |
| "top2:it": 32, | |
| "top1:fr": 52, | |
| "n": 190, | |
| "mean_router_entropy": 1.6838624473684212 | |
| }, | |
| "query:en": { | |
| "top1:en": 17, | |
| "top2:de": 49, | |
| "top1:de": 73, | |
| "top2:en": 47, | |
| "top2:fr": 26, | |
| "top1:it": 7, | |
| "top2:it": 14, | |
| "top2:rm": 3, | |
| "top1:fr": 43, | |
| "top2:gsw": 1, | |
| "n": 140, | |
| "mean_router_entropy": 1.7038726285714285 | |
| }, | |
| "query:fr": { | |
| "top1:de": 51, | |
| "top2:fr": 64, | |
| "top1:it": 47, | |
| "top2:de": 39, | |
| "top2:en": 21, | |
| "top1:fr": 90, | |
| "top1:en": 2, | |
| "top2:gsw": 2, | |
| "top2:it": 64, | |
| "n": 190, | |
| "mean_router_entropy": 1.6880721684210527 | |
| }, | |
| "query:gsw": { | |
| "top1:de": 75, | |
| "top2:fr": 27, | |
| "top2:gsw": 36, | |
| "top2:it": 3, | |
| "top2:en": 9, | |
| "top1:it": 3, | |
| "top2:de": 5, | |
| "top1:fr": 2, | |
| "n": 80, | |
| "mean_router_entropy": 1.6277479750000001 | |
| }, | |
| "query:it": { | |
| "top1:it": 125, | |
| "top2:de": 46, | |
| "top1:en": 2, | |
| "top2:it": 30, | |
| "top2:fr": 92, | |
| "top1:de": 50, | |
| "top2:en": 17, | |
| "top1:fr": 13, | |
| "top2:rm": 5, | |
| "n": 190, | |
| "mean_router_entropy": 1.6620954894736841 | |
| }, | |
| "query:rm": { | |
| "top1:it": 106, | |
| "top2:de": 22, | |
| "top1:de": 58, | |
| "top2:en": 9, | |
| "top2:it": 20, | |
| "top2:rm": 49, | |
| "top2:fr": 62, | |
| "top2:gsw": 8, | |
| "top1:fr": 6, | |
| "n": 170, | |
| "mean_router_entropy": 1.6873487411764707 | |
| } | |
| } | |
| } |