To use it, just install it and specify the number of sentences you'd like to compress a response to and whether you want to set this as the response length moving forwards too.

Tired of the overly wordy responses your agents throw at you? We just published a new skill called `less` that will help you get to the heart of your issues quicker.

GPU CLI 0.32.0 is here and GPU development now runs natively on Windows. The `gpu` can now run directly on Windows (no WSL!), including gpu init, gpu update, and the dashboard. + P2P powered by @iroh_n0

Then, just run `gpu use unsloth-studio` and wait for the build to finish. Now you're ready to go!

To use it, first install GPU-CLI

We're excited to announce we've just made working with #Unsloth Studio on cloud GPUs way easier with our new dedicated template. This means training and running models is as simple as working with your local device and as powerful as the hardware you want to use. #LLM #MLOps

3. Enable Dry Runs If an agent uses the incorrect command, it can cause real problems. Providing a `--dry-run` flag is a crucial safety net as it allows agents to validate the request locally and properly assess the result of their actions before pulling the trigger.

1. Raw JSON > Custom Flags While flags make passing arguments to the CLI easier for humans, agents prefer parsing the json in it's entirety. Add a `--json` path to commands so agents can pass the full API payload with zero translation loss.

That's it! You can now open the URL in your browser, add your sample audio and the script you want the voice to read and it'll create a downloadable audio output for you

Next, paste the following command in your terminal of choice

Then run `gpu run serverless deploy` and get your endpoint. Your server provider handles worker provisioning & scaling while you keep a single CLI flow for deployment, status checking, warming & deletion.