Update src/pipeline.py

src/pipeline.py

@@ -41,6 +41,9 @@ from diffusers.utils.import_utils import is_torch_npu_available
 from diffusers.utils.torch_utils import maybe_allow_in_graph
 from diffusers.models.embeddings import CombinedTimestepGuidanceTextProjEmbeddings, CombinedTimestepTextProjEmbeddings, FluxPosEmbed
 from diffusers.models.modeling_outputs import Transformer2DModelOutput
+from diffusers import FluxPipeline, FluxTransformer2DModel, GGUFQuantizationConfig
+from diffusers.loaders.single_file_utils import create_diffusers_t5_model_from_checkpoint
+from diffusers.loaders.single_file_model import FromOriginalModelMixin
 
 class BasicQuantization:
     def __init__(self, bits=1):
@@ -592,10 +595,16 @@ def load_pipeline() -> Pipeline:
 
     dtype, device = torch.bfloat16, "cuda"
     
-    text_encoder_2 = T5EncoderModel.from_pretrained(
-        "silentdriver/aadb864af9", revision = "060dabc7fa271c26dfa3fd43c16e7c5bf3ac7892", torch_dtype=torch.bfloat16
-    ).to(memory_format=torch.channels_last)
-
+    # text_encoder_2 = T5EncoderModel.from_pretrained(
+    #     "silentdriver/aadb864af9", revision = "060dabc7fa271c26dfa3fd43c16e7c5bf3ac7892", torch_dtype=torch.bfloat16
+    # ).to(memory_format=torch.channels_last)
+
+    t5_path = os.path.join(HF_HUB_CACHE, "models--manbeast3b--t5-v1_1-xxl-encoder-q8/snapshots/59c6c9cb99dcea42067f32caac3ea0836ef4c548/t5-v1_1-xxl-encoder-Q8_0.gguf")
+    # config_path = os.path.join(HF_HUB_CACHE, "models--black-forest--labs/FLUX.1-schnell/snapshots/741f7c3ce8b383c54771c7003378a50191e9efe9/text_encoder_2/config.json")
+    config_path = os.path.join(HF_HUB_CACHE, "models--black-forest-labs--FLUX.1-schnell/snapshots/741f7c3ce8b383c54771c7003378a50191e9efe9/")
+    import pdb; pdb.set_trace()
+    ckpt_t5 = load_single_file_checkpoint(t5_path,local_files_only=True)
+    import pdb; pdb.set_trace()
     
     
     vae = AutoencoderTiny.from_pretrained("silentdriver/7815792fb4", revision="bdb7d88ebe5a1c6b02a3c0c78651dd57a403fdf5", torch_dtype=dtype)