* Model: Implement basic lora support
* Add ability to load loras from config on launch
* Supports loading multiple loras and lora scaling
* Add function to unload loras
* Colab: Update for basic lora support
* Model: Test vram alloc after lora load, add docs
* Git: Add loras folder to .gitignore
* API: Add basic lora-related endpoints
* Add /loras/ endpoint for querying available loras
* Add /model/lora endpoint for querying currently loaded loras
* Add /model/lora/load endpoint for loading loras
* Add /model/lora/unload endpoint for unloading loras
* Move lora config-checking logic to main.py for better compat with API endpoints
* Revert bad CRLF line ending changes
* API: Add basic lora-related endpoints (fixed)
* Add /loras/ endpoint for querying available loras
* Add /model/lora endpoint for querying currently loaded loras
* Add /model/lora/load endpoint for loading loras
* Add /model/lora/unload endpoint for unloading loras
* Move lora config-checking logic to main.py for better compat with API endpoints
* Model: Unload loras first when unloading model
* API + Models: Cleanup lora endpoints and functions
Condenses down endpoint and model load code. Also makes the routes
behave the same way as model routes to help not confuse the end user.
Signed-off-by: kingbri <bdashore3@proton.me>
* Loras: Optimize load endpoint
Return successes and failures along with consolidating the request
to the rewritten load_loras function.
Signed-off-by: kingbri <bdashore3@proton.me>
---------
Co-authored-by: kingbri <bdashore3@proton.me>
Co-authored-by: DocShotgun <126566557+DocShotgun@users.noreply.github.com>
YAML is a more flexible format when it comes to configuration. Commandline
arguments are difficult to remember and configure especially for
an API with complicated commandline names. Rather than using half-baked
textfiles, implement a proper config solution.
Also add a progress bar when loading models in the commandline.
Signed-off-by: kingbri <bdashore3@proton.me>
