Feature Extraction
Transformers.js
ONNX
sentence-transformers
bert
medical
on-device
text-embeddings-inference
Instructions to use evum/lab-marker-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use evum/lab-marker-e5-small with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'evum/lab-marker-e5-small'); - sentence-transformers
How to use evum/lab-marker-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("evum/lab-marker-e5-small") 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:
- 77dc3d4fce0d076c99c0646439de3c9ecd4de828e88bd2425b832cb769a45340
- Size of remote file:
- 17.1 MB
- SHA256:
- ef04f2b385d1514f500e779207ace0f53e30895ce37563179e29f4022d28ca38
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