Sentence Similarity
Safetensors
sentence-transformers
PyLate
eurobert
ColBERT
multi-vector
feature-extraction
multilingual
late-interaction
retrieval
pretrained
loss:Distillation
custom_code
Instructions to use VAGOsolutions/SauerkrautLM-EuroColBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use VAGOsolutions/SauerkrautLM-EuroColBERT with sentence-transformers:
from pylate import models queries = [ "Which planet is known as the Red Planet?", "What is the largest planet in our solar system?", ] documents = [ ["Mars is the Red Planet.", "Venus is Earth's twin."], ["Jupiter is the largest planet.", "Saturn has rings."], ] model = models.ColBERT(model_name_or_path="VAGOsolutions/SauerkrautLM-EuroColBERT") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
File size: 1,528 Bytes
1bb3e08 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | {
"architectures": [
"EuroBertModel"
],
"attention_bias": false,
"attention_dropout": 0.0,
"auto_map": {
"AutoConfig": "EuroBERT/EuroBERT-210m--configuration_eurobert.EuroBertConfig",
"AutoModel": "EuroBERT/EuroBERT-210m--modeling_eurobert.EuroBertModel",
"AutoModelForMaskedLM": "EuroBERT/EuroBERT-210m--modeling_eurobert.EuroBertForMaskedLM",
"AutoModelForPreTraining": "EuroBERT/EuroBERT-210m--modeling_eurobert.EuroBertPreTrainedModel",
"AutoModelForSequenceClassification": "EuroBERT/EuroBERT-210m--modeling_eurobert.EuroBertForSequenceClassification",
"AutoModelForTokenClassification": "EuroBERT/EuroBERT-210m--modeling_eurobert.EuroBertForTokenClassification"
},
"bos_token": "<|begin_of_text|>",
"bos_token_id": 128000,
"clf_pooling": "late",
"eos_token": "<|end_of_text|>",
"eos_token_id": 128001,
"head_dim": 64,
"hidden_act": "silu",
"hidden_dropout": 0.0,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"mask_token": "<|mask|>",
"mask_token_id": 128002,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "eurobert",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"num_key_value_heads": 12,
"pad_token": "<|end_of_text|>",
"pad_token_id": 128001,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 250000,
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.51.0",
"use_cache": false,
"vocab_size": 128258
}
|