Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
colbert
late-interaction
retrieval
pylate
text-embeddings-inference
Instructions to use chungimungi/GLInt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use chungimungi/GLInt with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("chungimungi/GLInt") 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: 772 Bytes
4e1b7b3 | 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 | {
"__version__": {
"pytorch": "2.11.0+cu130",
"sentence_transformers": "5.5.1",
"transformers": "5.3.0"
},
"attend_to_expansion_tokens": false,
"default_prompt_name": null,
"do_query_expansion": false,
"document_length": 300,
"document_prefix": "[D] ",
"model_type": "SentenceTransformer",
"prompts": {
"document": "",
"query": ""
},
"query_length": 32,
"query_prefix": "[Q] ",
"similarity_fn_name": "MaxSim",
"skiplist_words": [
"!",
"\"",
"#",
"$",
"%",
"&",
"'",
"(",
")",
"*",
"+",
",",
"-",
".",
"/",
":",
";",
"<",
"=",
">",
"?",
"@",
"[",
"\\",
"]",
"^",
"_",
"`",
"{",
"|",
"}",
"~"
]
} |