Sentence Similarity
sentence-transformers
Safetensors
qwen3
feature-extraction
Generated from Trainer
dataset_size:18851
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Voctree/harrier-oss-v1-0.6b-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Voctree/harrier-oss-v1-0.6b-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Voctree/harrier-oss-v1-0.6b-finetuned") sentences = [ "Salt-grilled Boneless Galbi", "겉절이(1kg)", "경포대밥상(떡갈비)(1인)", "갈비살소금구이" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Voctree/harrier-oss-v1-0.6b-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Voctree/harrier-oss-v1-0.6b-finetuned/resolve/main/tokenizer.json
- Command line
-
hf download hf://Voctree/harrier-oss-v1-0.6b-finetuned/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Voctree/harrier-oss-v1-0.6b-finetuned/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 8efc6183aedc48f043b076d5225021dabcc5ee09f1386e160e5780451415bb18
- Size of remote file:
- 11.4 MB
- SHA256:
- 6cf519278622d854311452949ee197ff7afb0fbb1e0fa16cc307a959d8e61764
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