update two example scripts

examples/int4-flux.1-dev-offload.py

+import torch
+from diffusers import FluxPipeline
+
+from nunchaku import NunchakuFluxTransformer2dModel, NunchakuT5EncoderModel
+
+transformer = NunchakuFluxTransformer2dModel.from_pretrained(
+    "mit-han-lab/svdq-int4-flux.1-dev", offload=True
+)  # set offload to False if you want to disable offloading
+text_encoder_2 = NunchakuT5EncoderModel.from_pretrained("mit-han-lab/svdq-flux.1-t5")
+pipeline = FluxPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-dev", transformer=transformer, torch_dtype=torch.bfloat16
+)
+pipeline.enable_sequential_cpu_offload()  # remove this line if you want to disable the CPU offloading
+image = pipeline("A cat holding a sign that says hello world", num_inference_steps=50, guidance_scale=3.5).images[0]
+image.save("flux.1-dev.png")

examples/int4-flux.1-schnell-offload.py

+import torch
+from diffusers import FluxPipeline
+
+from nunchaku import NunchakuFluxTransformer2dModel, NunchakuT5EncoderModel
+
+transformer = NunchakuFluxTransformer2dModel.from_pretrained(
+    "mit-han-lab/svdq-int4-flux.1-schnell", offload=True
+)  # set offload to False if you want to disable offloading
+pipeline = FluxPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-schnell", transformer=transformer, torch_dtype=torch.bfloat16
+)
+pipeline.enable_sequential_cpu_offload()  # remove this line if you want to disable the CPU offloading
+image = pipeline(
+    "A cat holding a sign that says hello world", width=1024, height=1024, num_inference_steps=4, guidance_scale=0
+).images[0]
+image.save("flux.1-schnell.png")