Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:1042218
loss:CachedMultipleNegativesRankingLoss
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use chirag1701/resolve72-biencoder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use chirag1701/resolve72-biencoder-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("chirag1701/resolve72-biencoder-v1") sentences = [ "query: ironclad | 221 david street, burleson, tx", "query: red bike shop | ", "query: ironclad | 221 david st, burleson, texas", "query: g0lden massage | sudbury way, null, carmichael, ca" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from chirag1701/resolve72-biencoder-v1: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/chirag1701/resolve72-biencoder-v1/resolve/main/tokenizer.json
- Command line
-
hf download hf://chirag1701/resolve72-biencoder-v1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/chirag1701/resolve72-biencoder-v1/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 0e5e8194f58b9752ea875e6a5938c7d7ac928bd5912e0f9f98e18b5745d28265
- Size of remote file:
- 17.1 MB
- SHA256:
- 937f4a82d2465952cc36b8b530eff763b9bb84f82bbb0cacb81b8c1dc750e6d2
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