SomeStay07/vacancy-similarity-onnx
06
iOS Vacancy Similarity Model (ONNX)
Usage with @xenova/transformers
import { pipeline } from '@xenova/transformers';
// Load the model
const extractor = await pipeline(
'feature-extraction',
'/Users/timurceberda/Developer/telegram-ios-academy-foundation-pro/apps/miniapp/models/ios-vacancy-similarity-onnx',
{ local_files_only: true }
);
// Get embeddings
const vacancy1 = await extractor('iOS разработчик Swift UIKit');
const vacancy2 = await extractor('Разработчик мобильных приложений iOS');
// Calculate cosine similarity
function cosineSimilarity(a, b) {
let dot = 0, normA = 0, normB = 0;
for (let i = 0; i < a.length; i++) {
dot += a[i] * b[i];
normA += a[i] * a[i];
normB += b[i] * b[i];
}
return dot / (Math.sqrt(normA) * Math.sqrt(normB));
}
const similarity = cosineSimilarity(vacancy1.data, vacancy2.data);
console.log('Similarity:', similarity);Model Info
This model was fine-tuned on iOS developer vacancies from HH.ru for improved similarity matching in the iOS vacancy aggregator app.
Base model: sentence-transformers/all-MiniLM-L6-v2 Embedding dimension: 384 Training pairs: 2000+
