feat(diffusers): add support for Sana pipelines

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto 2025-01-14 09:40:33 +01:00
parent 62abe0d2c9
commit 328dd46867

View file

@ -17,7 +17,7 @@ import backend_pb2_grpc
import grpc
from diffusers import StableDiffusion3Pipeline, StableDiffusionXLPipeline, StableDiffusionDepth2ImgPipeline, DPMSolverMultistepScheduler, StableDiffusionPipeline, DiffusionPipeline, \
from diffusers import SanaPipeline, StableDiffusion3Pipeline, StableDiffusionXLPipeline, StableDiffusionDepth2ImgPipeline, DPMSolverMultistepScheduler, StableDiffusionPipeline, DiffusionPipeline, \
EulerAncestralDiscreteScheduler, FluxPipeline, FluxTransformer2DModel
from diffusers import StableDiffusionImg2ImgPipeline, AutoPipelineForText2Image, ControlNetModel, StableVideoDiffusionPipeline
from diffusers.pipelines.stable_diffusion import safety_checker
@ -275,6 +275,13 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
if request.LowVRAM:
self.pipe.enable_model_cpu_offload()
elif request.PipelineType == "SanaPipeline":
self.pipe = SanaPipeline.from_pretrained(
request.Model,
variant="bf16",
torch_dtype=torch.bfloat16)
self.pipe.vae.to(torch.bfloat16)
self.pipe.text_encoder.to(torch.bfloat16)
if CLIPSKIP and request.CLIPSkip != 0:
self.clip_skip = request.CLIPSkip