Add files using upload-large-folder tool

src/pipeline.py

@@ -1,7 +1,7 @@
 from diffusers import FluxPipeline, AutoencoderKL, AutoencoderTiny
 from diffusers.image_processor import VaeImageProcessor
 from diffusers.schedulers import FlowMatchEulerDiscreteScheduler
-
+from huggingface_hub.constants import HF_HUB_CACHE
 from transformers import T5EncoderModel, T5TokenizerFast, CLIPTokenizer, CLIPTextModel
 import torch
 import torch._dynamo
@@ -22,6 +22,7 @@ torch.backends.cudnn.enabled = True
 torch.backends.cudnn.benchmark = True
 
 ckpt_id = "black-forest-labs/FLUX.1-schnell"
+ckpt_revision = "741f7c3ce8b383c54771c7003378a50191e9efe9" 
 def empty_cache():
     gc.collect()
     torch.cuda.empty_cache()
@@ -32,20 +33,22 @@ def load_pipeline() -> Pipeline:
     empty_cache()
 
     dtype, device = torch.bfloat16, "cuda"
-
+    
     text_encoder_2 = T5EncoderModel.from_pretrained(
-        "city96/t5-v1_1-xxl-encoder-bf16", torch_dtype=torch.bfloat16
-    ).to(memory_format=torch.channels_last)
-    model = FluxTransformer2DModel.from_pretrained(
-        "/home/sandbox/.cache/huggingface/hub/models--RobertML--FLUX.1-schnell-int8wo/snapshots/307e0777d92df966a3c0f99f31a6ee8957a9857a", torch_dtype=dtype, use_safetensors=False
+        "city96/t5-v1_1-xxl-encoder-bf16", revision = "1b9c856aadb864af93c1dcdc226c2774fa67bc86", torch_dtype=torch.bfloat16
     ).to(memory_format=torch.channels_last)
+    
+
+    path = os.path.join(HF_HUB_CACHE, "models--RobertML--FLUX.1-schnell-int8wo/snapshots/307e0777d92df966a3c0f99f31a6ee8957a9857a")
+    model = FluxTransformer2DModel.from_pretrained(path, torch_dtype=dtype, use_safetensors=False).to(memory_format=torch.channels_last)
     pipeline = DiffusionPipeline.from_pretrained(
-        ckpt_id, 
+        ckpt_id,
+        revision=ckpt_revision,
         transformer=model,
-        text_encoder_2=text_encoder_2,
+        #text_encoder_2=text_encoder_2,
         torch_dtype=dtype,
         ).to(device)
-    #quantize_(pipeline.vae, int8_weight_only())
+    quantize_(pipeline.vae, int8_weight_only())
     for _ in range(3):
         pipeline(prompt="onomancy, aftergo, spirantic, Platyhelmia, modificator, drupaceous, jobbernowl, hereness", width=1024, height=1024, guidance_scale=0.0, num_inference_steps=4, max_sequence_length=256)
     

uv.lock

@@ -161,8 +161,8 @@ dependencies = [
     { name = "diffusers" },
     { name = "edge-maxxing-pipelines" },
     { name = "gitpython" },
+    { name = "hf-transfer" },
     { name = "omegaconf" },
-    { name = "opencv-python" },
     { name = "protobuf" },
     { name = "sentencepiece" },
     { name = "torch" },
@@ -176,12 +176,12 @@ requires-dist = [
     { name = "diffusers", specifier = "==0.31.0" },
     { name = "edge-maxxing-pipelines", git = "https://github.com/womboai/edge-maxxing?subdirectory=pipelines&rev=7c760ac54f6052803dadb3ade8ebfc9679a94589#7c760ac54f6052803dadb3ade8ebfc9679a94589" },
     { name = "gitpython", specifier = ">=3.1.43" },
+    { name = "hf-transfer", specifier = "==0.1.8" },
     { name = "omegaconf", specifier = "==2.3.0" },
-    { name = "opencv-python", specifier = ">=4.10.0.84" },
     { name = "protobuf", specifier = "==5.28.3" },
     { name = "sentencepiece", specifier = "==0.2.0" },
     { name = "torch", specifier = "==2.5.1" },
-    { name = "torchao", specifier = ">=0.6.1" },
+    { name = "torchao", specifier = "==0.6.1" },
     { name = "transformers", specifier = "==4.46.2" },
 ]
 
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