Public/automatic
1
0
Fork 0
mirror of https://github.com/vladmandic/automatic synced 2026-09-19 09:14:35 +02:00
Code Issues Packages Projects Releases Wiki Activity

Fix Nunchaku

Browse Source
This commit is contained in:
Disty0
2025-06-16 02:43:49 +03:00
parent 9c191e6796
commit 892dd456f7
2 changed files with 6 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files
CHANGELOG.md
+2 -1
View File
@@ -1,6 +1,6 @@
# Change Log for SD.Next
## Update for 2025-06-15
## Update for 2025-06-16
- **Feature**
- Support for Python 3.13
@@ -42,6 +42,7 @@
- TAESD previews with PixArt and Lumina 2
- VAE Tiling with non-default tile sizes
- Lumina 2 with IPEX
- Nunchaku updated repo
## Update for 2025-06-02
modules/model_flux.py
+4 -4
View File
@@ -115,11 +115,11 @@ def load_quants(kwargs, repo_id, cache_dir, allow_quant):
nunchaku_precision = nunchaku.utils.get_precision()
nunchaku_repo = None
if 'dev' in repo_id:
nunchaku_repo = f"mit-han-lab/svdq-{nunchaku_precision}-flux.1-dev"
nunchaku_repo = f"mit-han-lab/nunchaku-flux.1-dev/svdq-{nunchaku_precision}_r32-flux.1-dev.safetensors"
elif 'schnell' in repo_id:
nunchaku_repo = f"mit-han-lab/svdq-{nunchaku_precision}-flux.1-schnell"
nunchaku_repo = f"mit-han-lab/nunchaku-flux.1-schnell/svdq-{nunchaku_precision}_r32-flux.1-schnell.safetensors"
elif 'shuttle' in repo_id:
nunchaku_repo = 'mit-han-lab/svdq-fp4-shuttle-jaguar'
nunchaku_repo = f"mit-han-lab/nunchaku-shuttle-jaguar/svdq-{nunchaku_precision}_r32-shuttle-jaguar.safetensors"
else:
shared.log.error(f'Load module: quant=Nunchaku module=transformer repo="{repo_id}" unsupported')
if nunchaku_repo is not None:
@@ -135,7 +135,7 @@ def load_quants(kwargs, repo_id, cache_dir, allow_quant):
if 'text_encoder_2' not in kwargs and model_quant.check_nunchaku('TE'):
import nunchaku
nunchaku_precision = nunchaku.utils.get_precision()
nunchaku_repo = 'mit-han-lab/svdq-flux.1-t5'
nunchaku_repo = 'mit-han-lab/nunchaku-t5/awq-int4-flux.1-t5xxl.safetensors'
shared.log.debug(f'Load module: quant=Nunchaku module=t5 repo="{nunchaku_repo}" precision={nunchaku_precision}')
kwargs['text_encoder_2'] = nunchaku.NunchakuT5EncoderModel.from_pretrained(nunchaku_repo, torch_dtype=devices.dtype)
elif 'text_encoder_2' not in kwargs and model_quant.check_quant('TE'):