Product release
What’s new in Finetuner 0.6?
New CLIP models and ease of use make fine-tuning vector search tasks a breeze
We’re pleased to announce the launch of Jina AI’s Finetuner 0.6, which is now easier to use than ever.
Fine-tuning is an effective way to improve the performance on neural search tasks. However, handling the infrastructure is non-trivial.
Finetuner makes fine-tuning easier, faster and performant by streamlining the workflow and handling all complexity and infrastructure on the cloud. With Finetuner, you can easily uplift pre-trained models to be more performant and production ready.
Want to see how much better fine-tuning makes things? Check our benchmark:
New CLIP models
We now support the OpenCLIP family plus the Hugging Face variations like openai/clip-large-patch14
, openai/clip-vit-large-patch14–336
, and openai/clip-vit-base-patch16
. To check the full list (30+), simply call finetuner.describe_models()
.
Easier to use
We heard your feedback and we saw it was very difficult to use a Finetuner if you were not using Jina. In this release, less is more. You can see how much easier it is to use a fine-tuned model:
Use your fine-tuned model with Jina
There are many ways you can use your finetuned model with Jina. Below we’ve outlined just two.
- Log in
- Get your token
- Get your run
- Use your artifact
Fine-tune and use your model without Jina
You also cannot use Jina if you need a more lightweight experience that just uses DocArray. Again, it’s as simple as:
- Log in
- Fit your model
- Stream your logs
- Save your artifact
- Get your model
- Encode your data
Get started now
- Head to the Finetuner website to read tutorials on finetuning text-to-text, image-to-image and text-to-image search.
- Check out the Genshin Impact finetuner notebook.
- The first time you call
finetuner.login()
you’ll be prompted to create a Jina AI account.