Sentence Similarity
sentence-transformers
Safetensors
distilbert
feature-extraction
dense
Generated from Trainer
dataset_size:3810
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use SwarajSolanke-turtle/make-model-SimCSE-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SwarajSolanke-turtle/make-model-SimCSE-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SwarajSolanke-turtle/make-model-SimCSE-embedding") sentences = [ "bmw ix", "bmw ix", "bmw x7", "bmw i5" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from SwarajSolanke-turtle/make-model-SimCSE-embedding: direct link, hf CLI and curl.
- Browser
- Download file 284 Bytes
-
https://huggingface.co/SwarajSolanke-turtle/make-model-SimCSE-embedding/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://SwarajSolanke-turtle/make-model-SimCSE-embedding/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/SwarajSolanke-turtle/make-model-SimCSE-embedding/resolve/main/config_sentence_transformers.json
284 Bytes
| { | |
| "__version__": { | |
| "pytorch": "2.14.1+cu130", | |
| "sentence_transformers": "6.1.0", | |
| "transformers": "5.20.1" | |
| }, | |
| "default_prompt_name": null, | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "document": "", | |
| "query": "" | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |