Sentence Similarity
sentence-transformers
ONNX
Safetensors
Transformers.js
gte
feature-extraction
mteb
arctic
snowflake-arctic-embed
custom_code
Eval Results (legacy)
Instructions to use aynetdia/snowflake-arctic-embed-m-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use aynetdia/snowflake-arctic-embed-m-v2.0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("aynetdia/snowflake-arctic-embed-m-v2.0", 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.js
How to use aynetdia/snowflake-arctic-embed-m-v2.0 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('sentence-similarity', 'aynetdia/snowflake-arctic-embed-m-v2.0'); - Notebooks
- Google Colab
- Kaggle
File size: 1,073 Bytes
6bcf851 | 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 | {
"architectures": [
"GteModel"
],
"attention_probs_dropout_prob": 0.0,
"auto_map": {
"AutoConfig": "configuration_hf_alibaba_nlp_gte.GteConfig",
"AutoModel": "modeling_hf_alibaba_nlp_gte.GteModel",
"AutoModelForSequenceClassification": "modeling_hf_alibaba_nlp_gte.GteForSequenceClassification"
},
"classifier_dropout": 0.1,
"hidden_act": "gelu",
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"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"layer_norm_type": "layer_norm",
"logn_attention_clip1": false,
"logn_attention_scale": false,
"max_position_embeddings": 8192,
"model_type": "gte",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pack_qkv": true,
"pad_token_id": 1,
"position_embedding_type": "rope",
"rope_scaling": null,
"rope_theta": 160000,
"torch_dtype": "float32",
"transformers_version": "4.39.3",
"type_vocab_size": 1,
"unpad_inputs": "true",
"use_memory_efficient_attention": "true",
"matryoshka_dimensions": [256],
"vocab_size": 250048
}
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