Sentence Similarity
sentence-transformers
Safetensors
English
nomic_bert
feature-extraction
Generated from Trainer
dataset_size:35964
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use ITOCJ/SciTopicNomicEmbed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ITOCJ/SciTopicNomicEmbed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ITOCJ/SciTopicNomicEmbed", trust_remote_code=True) sentences = [ "Despite the crucial role of phosphorus in global food production, there is a lack of comprehensive analysis on the economic and policy aspects of phosphorus supply and demand, highlighting a significant knowledge gap in the field of natural resource economics.", "The human brain is intrinsically organized into dynamic, anticorrelated functional networks", "The story of phosphorus: Global food security and food for thought", "Identifying a knowledge gap in the field of study" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 1,221 Bytes
b94be35 | 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 | {
"added_tokens_decoder": {
"0": {
"content": "[PAD]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"100": {
"content": "[UNK]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"101": {
"content": "[CLS]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"102": {
"content": "[SEP]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"103": {
"content": "[MASK]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"clean_up_tokenization_spaces": true,
"cls_token": "[CLS]",
"do_lower_case": true,
"extra_special_tokens": {},
"mask_token": "[MASK]",
"model_max_length": 8192,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"unk_token": "[UNK]"
}
|