A lightweight open-source package to fine-tune embedding models.
Project description
Embedding Adapter 💬 📐
Finetune embedding models in just 4 lines of code.
from embedding_adapter import EmbeddingAdapter
adapter = EmbeddingAdapter()
EmbeddingAdapter.fit(query_embeddings, document_embeddings, labels)
EmbeddingAdapter.transform(new_embeddings)
Once you've trained the adapter, you can use patch your pre-trained embedding model.
patch = EmbeddingAdapter.patch()
adapted_embeddings = patch(original_embedding_fn("SAMPLE_TEXT"))
Synthetic Label Generation
No user feedback to use as labels? 🤔 Create synthetic label the LabelGenerator
util
from embedding_adapter.utils import LabelGenerator
generator = LabelGenerator()
generator.run()
Note: This requires an OpenAI API key saved as an OPENAI_API_KEY
env var.
Installation 🔧
pip install embedding_adapter
License 📄
This project is licensed under the MIT License.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for embedding_adapter-0.1.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5fd7513bb7af764cf09451936b9645b946c4d89d808154fd0cd1d618f41a9b0e |
|
MD5 | 5d10b739418259a7781c971e44b5e0e0 |
|
BLAKE2b-256 | 183a85ed20df4779194ba839ff77528b0405c2bae48fe83849e0b2c99914d70e |