Instructions to use ilyaplusplus/F2LLM-v2-80M-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use ilyaplusplus/F2LLM-v2-80M-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'ilyaplusplus/F2LLM-v2-80M-ONNX'); - sentence-transformers
How to use ilyaplusplus/F2LLM-v2-80M-ONNX with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ilyaplusplus/F2LLM-v2-80M-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
- Xet hash:
- 9c2268ef2dbd8cb158ceef8efa326a348c3b1645c00ecfae555870e6f48ce8c2
- Size of remote file:
- 11.4 MB
- SHA256:
- 38360d5a512a43641b36d6fba2df87b8a3f5464c6b5c76f03e82d6d795175566
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