Sentence Similarity
sentence-transformers
Safetensors
Transformers
new
feature-extraction
mteb
multilingual
text-embeddings-inference
custom_code
Eval Results (legacy)
Instructions to use yankexe/gte-multilingual-base-air-gapped with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yankexe/gte-multilingual-base-air-gapped with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yankexe/gte-multilingual-base-air-gapped", 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] - Transformers
How to use yankexe/gte-multilingual-base-air-gapped with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yankexe/gte-multilingual-base-air-gapped", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,275 Bytes
19cfb7a 930959e 19cfb7a | 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 | {
"architectures": [
"NewModel",
"NewForTokenClassification"
],
"attention_probs_dropout_prob": 0.0,
"auto_map": {
"AutoConfig": "configuration.NewConfig",
"AutoModelForMaskedLM": "modeling.NewForMaskedLM",
"AutoModel": "modeling.NewModel",
"AutoModelForMultipleChoice": "modeling.NewForMultipleChoice",
"AutoModelForQuestionAnswering": "modeling.NewForQuestionAnswering",
"AutoModelForSequenceClassification": "modeling.NewForSequenceClassification",
"AutoModelForTokenClassification": "modeling.NewForTokenClassification"
},
"classifier_dropout": 0.0,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"layer_norm_type": "layer_norm",
"max_position_embeddings": 8192,
"model_type": "new",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"num_labels": 1,
"pack_qkv": true,
"pad_token_id": 1,
"position_embedding_type": "rope",
"rope_scaling": {
"factor": 8.0,
"type": "ntk"
},
"rope_theta": 20000,
"torch_dtype": "float16",
"transformers_version": "4.39.1",
"type_vocab_size": 1,
"unpad_inputs": false,
"use_memory_efficient_attention": false,
"vocab_size": 250048
}
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