Finetuner 0.8.1 Update
Finetuner makes neural network fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure requirements in the cloud.
This release covers Finetuner version 0.8.1, including dependency finetuner-core 0.13.10.
This release contains 1 new feature, 1 refactoring and 1 documentation improvement.
jina-ai🆕 Features
Add Jina Tiny Embedding model
We have included jina-embedding-t-en-v1 in our list of supported models. This very small embedding model, comprising 14 million parameters, offers lightning-fast inference on CPUs.
In our experiments, it was able to encode 1730 sentences per second on a Macbook Pro Core-i5, making it perfectly suitable for edge devices. To utilize the Tiny model, follow these steps:
!pip install finetuner
import finetuner
model = finetuner.build_model('jinaai/jina-embedding-t-en-v1')
embeddings = finetuner.encode(
model=model,
data=['how is the weather today', 'What is the current weather like today?']
)
print(finetuner.cos_sim(embeddings[0], embeddings[1]))⚙ Refactoring
Remove typing-extensions from Finetuner dependencies
We have eliminated the dependency on typing-extensions due to compatibility issues when using the Finetuner on Google Colab.
📗 Documentation Improvements
Add Tiny model and technical report to Finetuner Readme and Docs. (#763)
We have updated the documentation page to include information about jina-embedding-t-en-v1. We have also added technical reports and citation details tothe README and documentation page.
🤟 Contributors
We would like to thank all contributors to this release:
- Wang Bo (@bwanglzu)
- Louis Milliken (@LMMilliken)
- Michael Günther (@guenthermi)
- George Mastrapas (@gmastrapas)
- Scott Martens (@scott-martens)