Sometimes, diffusers model components (tokenizer, unet, etc.) have multiple weights files in the same directory.
In this situation, we assume the files are different versions of the same weights. For example, we may have multiple
formats (`.bin`, `.safetensors`) with different precisions. When downloading model files, we want to select only
the best of these files for the requested format and precision/variant.
The previous logic assumed that each model weights file would have the same base filename, but this assumption was
not always true. The logic is revised score each file and choose the best scoring file, resulting in only a single
file being downloaded for each submodel/subdirectory.
* UI in MM to create trigger phrases
* add scheduler and vaePrecision to config
* UI for configuring default settings for models'
* hook MM default model settings up to API
* add button to set default settings in parameters
* pull out trigger phrases
* back-end for default settings
* lint
* remove log;
gi
* ruff
* ruff format
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Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
- Use memory view for hashlib algorithms (closer to python 3.11's filehash API in hashlib)
- Remove `sha1_fast` (realized it doesn't even hash the whole file, it just does the first block)
- Add support for custom file filters
- Update docstrings
- Update tests
- When installing, model keys are now calculated from the model contents.
- .safetensors, .ckpt and other single file models are hashed with sha1
- The contents of diffusers directories are hashed using imohash (faster)
fixup yaml->sql db migration script to assign deterministic key
- this commit also detects and assigns the correct image encoder for
ip adapter models.
The setup of `ModelConfigBase` means autogenerated types have critical fields flagged as nullable (like `key` and `base`). Need to manually flag them as required.
- Replace AnyModelLoader with ModelLoaderRegistry
- Fix type check errors in multiple files
- Remove apparently unneeded `get_model_config_enum()` method from model manager
- Remove last vestiges of old model manager
- Updated tests and documentation
resolve conflict with seamless.py
- Rename old "model_management" directory to "model_management_OLD" in order to catch
dangling references to original model manager.
- Caught and fixed most dangling references (still checking)
- Rename lora, textual_inversion and model_patcher modules
- Introduce a RawModel base class to simplfy the Union returned by the
model loaders.
- Tidy up the model manager 2-related tests. Add useful fixtures, and
a finalizer to the queue and installer fixtures that will stop the
services and release threads.