Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
dense
Generated from Trainer
dataset_size:58800
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Shuu12121/CodeSearch-ModernBERT-Finch-SmallBatch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Shuu12121/CodeSearch-ModernBERT-Finch-SmallBatch with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Shuu12121/CodeSearch-ModernBERT-Finch-SmallBatch") sentences = [ "Returns boolean indicating whether the requestUrl matches against the paths configured.\n\n@param requestedUrl - url requested by user\n@param opts - unless configuration\n@returns {boolean}", "def xmoe2_v1_l4k_global_only():\n \"\"\"\"\"\"\n hparams = xmoe2_v1_l4k()\n hparams.decoder_layers = [\n \"att\" if l == \"local_att\" else l for l in hparams.decoder_layers]\n return hparams", "function matchesPath(requestedUrl, opts) {\n var paths = !opts.path || Array.isArray(opts.path) ?\n opts.path : [opts.path];\n\n if (paths) {\n return paths.some(function(p) {\n return (typeof p === 'string' && p === requestedUrl.pathname) ||\n (p instanceof RegExp && !! p.exec(requestedUrl.pathname));\n });\n }\n\n return false;\n}", "public static function factory($accessToken, $currentTeam)\n {\n $client = Client::factory($accessToken);\n\n return new self($client, $currentTeam);\n }" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 1,398 Bytes
6b0a938 | 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 | {
"add_prefix_space": false,
"added_tokens_decoder": {
"30000": {
"content": "<s>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"30001": {
"content": "</s>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"30002": {
"content": "<unk>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"30003": {
"content": "<pad>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"30004": {
"content": "<mask>",
"lstrip": true,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"bos_token": "<s>",
"clean_up_tokenization_spaces": false,
"cls_token": "<s>",
"eos_token": "</s>",
"errors": "replace",
"extra_special_tokens": {},
"mask_token": "<mask>",
"max_length": 256,
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<pad>",
"sep_token": "</s>",
"stride": 0,
"tokenizer_class": "RobertaTokenizer",
"trim_offsets": true,
"truncation_side": "right",
"truncation_strategy": "longest_first",
"unk_token": "<unk>"
}
|