Instructions to use SoTrxII/analytical-pattern-embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SoTrxII/analytical-pattern-embedder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SoTrxII/analytical-pattern-embedder") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 2,354 Bytes
ad7feb3 | 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 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 | {
"architectures": [
"EmbeddingGemma2Model"
],
"audio_config": null,
"audio_token_id": 258881,
"boa_token_id": 256000,
"boi_token_id": 255999,
"dtype": "bfloat16",
"eoa_token_index": 258883,
"eoi_token_id": 258882,
"image_token_id": 258880,
"initializer_range": 0.02,
"model_type": "embedding_gemma2",
"text_config": {
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 2,
"dtype": "bfloat16",
"embedding_dim": 768,
"eos_token_id": 1,
"head_dim": 256,
"hidden_activation": "gelu_pytorch_tanh",
"hidden_size": 512,
"hidden_size_per_layer_input": 512,
"initializer_range": 0.02,
"intermediate_size": 2048,
"layer_types": [
"sliding_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"sliding_attention",
"full_attention"
],
"max_position_embeddings": 262144,
"model_type": "embedding_gemma2_text",
"num_attention_heads": 4,
"num_hidden_layers": 24,
"num_key_value_heads": 2,
"pad_token_id": 0,
"per_layer_config": {
"05": {
"head_dim": 512,
"num_key_value_heads": 1
},
"11": {
"head_dim": 512,
"num_key_value_heads": 1
},
"17": {
"head_dim": 512,
"num_key_value_heads": 1
},
"23": {
"head_dim": 512,
"num_key_value_heads": 1
}
},
"rms_norm_eps": 1e-06,
"rope_parameters": {
"full_attention": {
"rope_theta": 1000000.0,
"rope_type": "default"
},
"sliding_attention": {
"rope_theta": 10000.0,
"rope_type": "default"
}
},
"sliding_window": 512,
"vocab_size": 262144
},
"transformers_version": "5.19.0",
"video_token_id": 258884,
"vision_config": null,
"vision_soft_tokens_per_image": 280
}
|