Disty0

/

LTX-2-SDNQ-4bit-dynamic

like 10

KeyError                                  Traceback (most recent call last)
Cell In[2], line 7
      4 from sdnq.common import use_torch_compile as triton_is_available
      5 from sdnq.loader import apply_sdnq_options_to_model
----> 7 pipe = diffusers.LTX2Pipeline.from_pretrained("Disty0/LTX-2-SDNQ-4bit-dynamic", torch_dtype=torch.bfloat16)
      9 # Enable INT8 MatMul for AMD, Intel ARC and Nvidia GPUs:
     10 # if triton_is_available and (torch.cuda.is_available() or torch.xpu.is_available()):
     11 #     pipe.transformer = apply_sdnq_options_to_model(pipe.transformer, use_quantized_matmul=True)
     12 #     pipe.text_encoder = apply_sdnq_options_to_model(pipe.text_encoder, use_quantized_matmul=True)
     13     # pipe.transformer = torch.compile(pipe.transformer) # optional for faster speeds
     15 pipe.vae.enable_tiling()

File ~/LatentSpaceJam/.venv/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    111 if check_use_auth_token:
    112     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)

File ~/LatentSpaceJam/.venv/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py:1021, in DiffusionPipeline.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
   1014 else:
   1015     # load sub model
   1016     sub_model_dtype = (
   1017         torch_dtype.get(name, torch_dtype.get("default", torch.float32))
   1018         if isinstance(torch_dtype, dict)
   1019         else torch_dtype
...
    229 )
    231 if layer_class_name in conv_types:
    232     is_conv_type = True

KeyError: 'float5_e3m1fn'