v5.10.1
invoke-ai/InvokeAIv5.10.1Apr 19, 2025by psychedelicious
Upgrading?
Release notes summary
This patch release fixes critical crashes related to partial loading of LLaVA and SigLIP models and reverts a change that could misidentify models as LoRAs.
Key Highlights
- Partial loading support for LLaVA and SigLIP models
- Fixed hard crash on initial load for specific models
- Reverted model identification bug
New Features
- Partial Model Loading (LLaVA, SigLIP)
Full Release Notes
#### π¨ Achtung! π¨
> If you already updated to v5.10.0, you can skip this section. If you are on v5.9.1 or older, please review this section before updating.
There are important installation notes to be aware of in this release, which includes major updates to Invoke's core components.
1. **You must use the latest installer/launcher (v1.5.0). If youβre using an older launcher version, the update may fail.**
To fix this, download the latest installer/launcher from https://invoke.com/downloads.
2. **If the installation fails, use **repair mode** to fix it.**
The installation may fail due to Python environment conflicts with log messages like those in [this screenshot](https://github.com/user-attachments/assets/e0cecfe3-fc96-46fb-909e-b175d8a2e2b5).
To fix this, retry the installation with **repair mode** enabled, which will reinstall the bundled Python and resolve most installation issues.
Enable **repair mode** by ticking [this checkbox on the **Review** step of the install](https://github.com/user-attachments/assets/45492acc-2f63-4d53-876b-17a497462178), then click **Install**.
3. **Form Builder reset on first launch.**
When you start Invoke for the first time after updating to v5.10.0, your Form Builder will be reset, losing any unsaved changes.
Before updating, save your current workflow. After updating, re-load it manually.
## Changes
- Support partial loading for LLaVA and SigLIP (FLUX Redux) models, reducing VRAM requirements for users with Nvidia GPUs.
- Reduce peak CPU RAM usage during initial load of LLaVA and SigLIP models. This allows users with at least 24GB CPU RAM to run the LLaVA 7B model without crashing during load. With partial loading now working for the model, most users should be able to run the model - though it can take a few minutes if you don't have a GPU with 24GB VRAM.
- Revert a recent change to model installation, which could result in some models being misidentified as LoRAs.
- The data viewer component, used to display JSON (e.g. metadata, workflows, node outputs) now wraps lines.
## Installing and Updating
**The new Invoke Launcher is the recommended way to install, update and run Invoke**. It takes care of a lot of details for you - like installing the right version of python - and runs Invoke as a desktop application.
Follow the [Quick Start guide](https://invoke-ai.github.io/InvokeAI/installation/quick_start/) to get started with the launcher.
If you don't want to use the launcher, or need a headless install, you can follow the [manual install guide](https://invoke-ai.github.io/InvokeAI/installation/manual/).
## What's Changed
* feat(ui): wrap JSON in dataviewer by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/7930
* fix(mm): partial loading for LLaVA and SigLIP models, hard crash on initial load by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/7929
* fix(mm): disable new model probe API by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/7940
* chore: bump version to v5.10.1 by @psychedelicious in https://github.com/invoke-ai/InvokeAI/pull/7941
**Full Changelog**: https://github.com/invoke-ai/InvokeAI/compare/v5.10.0...v5.10.1Related Repositories
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