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
| { | |
| "experiment_mode": "moe_head", | |
| "source_model": "swiss-ai/Apertus-v1.1-0.5B", | |
| "dense_parent": "andreasmartin/apertus-v1.1-swiss-embed-0.4b-bidir", | |
| "dense_parent_revision": "875c1f99d7b20e261ea43b3586fdde5f8d5648e5", | |
| "backbone_frozen_during_moe_training": true, | |
| "training_profile": "quality", | |
| "data_recipe_signature": "fd8f7d87d50416d4d732c68dfffd2ce3de5a58aac879ccb677185d06186c400e", | |
| "train_moe_sha256": "287bee32718f74d333f48e94c38e5150ed70921f47e15871940c83ce7e13d22a", | |
| "dataset_revisions": { | |
| "wikimedia/wikipedia": "b04c8d1ceb2f5cd4588862100d08de323dccfbaa", | |
| "ZurichNLP/SwissGov-RSD": "f16aa0536811b8c0cf975fede21eec5996e4b3c1", | |
| "eljuanina/VotingBooklets-v1": "8db11c674d6993aee084fe65ed3ab6d9ee102fd7", | |
| "eljuanina/VotingBooklets-Diamond-v1": "476c96e74a72b65122cf6fc01943be125f7f3324" | |
| }, | |
| "training_triplets": 31483, | |
| "unique_prompted_texts": 56324, | |
| "moe_training_max_seq_length": 512, | |
| "inference_max_seq_length": 1024, | |
| "expert_names": [ | |
| "de", | |
| "en", | |
| "fr", | |
| "it", | |
| "rm", | |
| "gsw", | |
| "shared" | |
| ], | |
| "top_k": 2, | |
| "router_temperature": 1.0, | |
| "language_loss_weight": 0.05, | |
| "balance_loss_weight": 0.01, | |
| "head_learning_rate": 0.0002, | |
| "head_batch_size": 1024, | |
| "head_epochs": 5, | |
| "matryoshka_dims": [ | |
| 1024, | |
| 768, | |
| 512, | |
| 256 | |
| ], | |
| "matryoshka_weights": [ | |
| 1.0, | |
| 0.75, | |
| 0.5, | |
| 0.25 | |
| ], | |
| "training_history": [ | |
| { | |
| "epoch": 1, | |
| "loss": 2.023314436276754, | |
| "retrieval_loss": 1.9348004142443338, | |
| "language_loss": 1.7696655670801797, | |
| "balance_loss": 0.0030751408770205066, | |
| "lr": 0.00018090169943749468 | |
| }, | |
| { | |
| "epoch": 2, | |
| "loss": 1.9000611066818238, | |
| "retrieval_loss": 1.8191587686538697, | |
| "language_loss": 1.616682501633962, | |
| "balance_loss": 0.006820600215966503, | |
| "lr": 0.00013090169943749468 | |
| }, | |
| { | |
| "epoch": 3, | |
| "loss": 1.8358161449432373, | |
| "retrieval_loss": 1.7584825873374939, | |
| "language_loss": 1.5452160716056824, | |
| "balance_loss": 0.007276078267022967, | |
| "lr": 6.909830056250522e-05 | |
| }, | |
| { | |
| "epoch": 4, | |
| "loss": 1.7946220676104228, | |
| "retrieval_loss": 1.7193971276283264, | |
| "language_loss": 1.5032105565071106, | |
| "balance_loss": 0.00644152524570624, | |
| "lr": 1.909830056250526e-05 | |
| }, | |
| { | |
| "epoch": 5, | |
| "loss": 1.7804000655810037, | |
| "retrieval_loss": 1.7059372186660766, | |
| "language_loss": 1.4880693872769675, | |
| "balance_loss": 0.0059369114848474664, | |
| "lr": 0.0 | |
| } | |
| ] | |
| } |