Paulescu/text-embedding-evaluation
Join 15k builders to the Real-World ML Newsletter ⬇️⬇️⬇️
This tool helps machine learning practitioners or data scientists choose the best text embedding model for their specific retrieval tasks. You input your dataset of questions, contexts, and correct answers, along with a list of candidate embedding models. The tool outputs an evaluation of how well each model retrieves relevant information, helping you identify the top performer for your application.
No commits in the last 6 months.
Use this if you need to reliably find the most relevant documents for a given query and want to ensure you're using the optimal text embedding model for that purpose.
Not ideal if your primary use case for embeddings is classification or clustering, rather than information retrieval.
Stars
18
Forks
2
Language
Python
License
—
Category
Last pushed
Apr 19, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/Paulescu/text-embedding-evaluation"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Featured in
Higher-rated alternatives
embeddings-benchmark/mteb
MTEB: Massive Text Embedding Benchmark
harmonydata/harmony
The Harmony Python library: a research tool for psychologists to harmonise data and...
yannvgn/laserembeddings
LASER multilingual sentence embeddings as a pip package
embeddings-benchmark/results
Data for the MTEB leaderboard
Hironsan/awesome-embedding-models
A curated list of awesome embedding models tutorials, projects and communities.