Feature Extraction
Transformers.js
ONNX
sentence-transformers
xlm-roberta
sentence-similarity
embeddings
multilingual
text-embeddings-inference
Instructions to use yuiseki/granite-embedding-278m-multilingual-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use yuiseki/granite-embedding-278m-multilingual-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'yuiseki/granite-embedding-278m-multilingual-ONNX'); - sentence-transformers
How to use yuiseki/granite-embedding-278m-multilingual-ONNX with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yuiseki/granite-embedding-278m-multilingual-ONNX") 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
Ctrl+K