Feature Extraction
sentence-transformers
PyTorch
Russian
xlm-roberta
quantization
int8
cpu-optimized
text-embeddings-inference
Instructions to use koryl/bge-m3-quantized-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use koryl/bge-m3-quantized-int8 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("koryl/bge-m3-quantized-int8") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99cf9d2c1ad765677e0d599ec57c4330263f50bb282206893900ab282a0b4ae8
- Size of remote file:
- 1.36 GB
- SHA256:
- 247b6046adcc65dc024cc996bf29593408642083e450b39bb3c1d94463a580f0
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