Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
dense
Generated from Trainer
dataset_size:283621
loss:CachedMultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use benjamintli/modernbert-code-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use benjamintli/modernbert-code-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("benjamintli/modernbert-code-v2") sentences = [ "// Uint is a helper routine that allocates a new uint value to store v and\n// returns a pointer to it. This is useful when assigning optional parameters.", "func (c *Animation) GetCurrentTimeWithParams(v *AnimationGetCurrentTimeParams) (float64, error) {\n\tresp, err := gcdmessage.SendCustomReturn(c.target, c.target.GetSendCh(), &gcdmessage.ParamRequest{Id: c.target.GetId(), Method: \"Animation.getCurrentTime\", Params: v})\n\tif err != nil {\n\t\treturn 0, err\n\t}\n\n\tvar chromeData struct {\n\t\tResult struct {\n\t\t\tCurrentTime float64\n\t\t}\n\t}\n\n\tif resp == nil {\n\t\treturn 0, &gcdmessage.ChromeEmptyResponseErr{}\n\t}\n\n\t// test if error first\n\tcerr := &gcdmessage.ChromeErrorResponse{}\n\tjson.Unmarshal(resp.Data, cerr)\n\tif cerr != nil && cerr.Error != nil {\n\t\treturn 0, &gcdmessage.ChromeRequestErr{Resp: cerr}\n\t}\n\n\tif err := json.Unmarshal(resp.Data, &chromeData); err != nil {\n\t\treturn 0, err\n\t}\n\n\treturn chromeData.Result.CurrentTime, nil\n}", "func Uint(v uint) *uint {\n\tp := new(uint)\n\t*p = v\n\treturn p\n}", "def after_init_app(self, app: FlaskUnchained):\n \"\"\"\n Configure the JSON encoder for Flask to be able to serialize Enums,\n LocalProxy objects, and SQLAlchemy models.\n \"\"\"\n self.set_json_encoder(app)\n app.before_first_request(self.register_model_resources)" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K