Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
dense
Generated from Trainer
dataset_size:5002
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use yasserrmd/hindi-gemma-300m-emb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yasserrmd/hindi-gemma-300m-emb with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yasserrmd/hindi-gemma-300m-emb") sentences = [ "कालक्रम के विषय में कल्हण की सीमाएँ क्या हैं?", "विभिन्न प्रकार के धातुओं, काग़ज़, व प्लास्टिक को मिश्रण में से छांटा जाता है", "प्रारंभिक वंशावलियों", "फलोदी" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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