Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:225516
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use 2ADT-Consulting/susu-sentence-encoder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use 2ADT-Consulting/susu-sentence-encoder-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("2ADT-Consulting/susu-sentence-encoder-v1") sentences = [ "Il leur donna cet ordre: «Vous transmettrez ce message à mon seigneur Esaü: Voici ce que dit ton serviteur Jacob: J'ai séjourné chez Laban et j'y suis resté jusqu'à maintenant.", "I na fe nde to, i naxa gbata sigafe ra kiiti banxi, barima xa fe gbɛtɛ minima i mu naxan kolon, na nɔma i rayaagide i dɔxɔboore ya xɔri.", "Wo xa sɔɔrie luxi nɛ alɔ tugumi naxee na tɛtɛ fari gɛɛsɛgɛ, kɔnɔ soge na te, e tugan, e siga yire mixi mu dɛnnaxɛ kolon.", "A naxa a fala e bɛ, «Wo yi nan falama n marigi Esayu bɛ, ‹I xa konyi di Yaxuba naxɛ, N bara bu Laban xɔnyi han ya." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Add bilingual (fr/en-sus) sentence encoder fine-tuned with MNRL on paraphrase-multilingual-MiniLM-L12-v2
cdd2b74 verified | { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 384, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "is_decoder": false, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.0.0", | |
| "type_vocab_size": 2, | |
| "use_cache": false, | |
| "vocab_size": 250037 | |
| } | |