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https://github.com/comfyanonymous/ComfyUI.git
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2
.github/workflows/stable-release.yml
vendored
2
.github/workflows/stable-release.yml
vendored
@ -117,7 +117,7 @@ jobs:
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./python.exe get-pip.py
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./python.exe -s -m pip install ../${{ inputs.cache_tag }}_python_deps/*
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grep comfyui ../ComfyUI/requirements.txt > ./requirements_comfyui.txt
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grep comfy ../ComfyUI/requirements.txt > ./requirements_comfyui.txt
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./python.exe -s -m pip install -r requirements_comfyui.txt
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rm requirements_comfyui.txt
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@ -240,7 +240,7 @@ These have less hardware support than the builds above but they work on windows.
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RDNA 3 (RX 7000 series):
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```pip install --pre torch torchvision torchaudio --index-url https://rocm.nightlies.amd.com/v2/gfx110X-dgpu/```
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```pip install --pre torch torchvision torchaudio --index-url https://rocm.nightlies.amd.com/v2/gfx110X-all/```
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RDNA 3.5 (Strix halo/Ryzen AI Max+ 365):
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@ -36,10 +36,10 @@ class LTXAVGemmaTokenizer(sd1_clip.SD1Tokenizer):
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class Gemma3_12BModel(sd1_clip.SDClipModel):
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def __init__(self, device="cpu", layer="all", layer_idx=None, dtype=None, attention_mask=True, model_options={}):
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llama_scaled_fp8 = model_options.get("gemma_scaled_fp8", None)
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if llama_scaled_fp8 is not None:
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llama_quantization_metadata = model_options.get("llama_quantization_metadata", None)
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if llama_quantization_metadata is not None:
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model_options = model_options.copy()
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model_options["scaled_fp8"] = llama_scaled_fp8
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model_options["quantization_metadata"] = llama_quantization_metadata
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super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config={}, dtype=dtype, special_tokens={"start": 2, "pad": 0}, layer_norm_hidden_state=False, model_class=comfy.text_encoders.llama.Gemma3_12B, enable_attention_masks=attention_mask, return_attention_masks=attention_mask, model_options=model_options)
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@ -119,12 +119,12 @@ class LTXAVTEModel(torch.nn.Module):
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return self.load_state_dict(sdo, strict=False)
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def ltxav_te(dtype_llama=None, llama_scaled_fp8=None):
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def ltxav_te(dtype_llama=None, llama_quantization_metadata=None):
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class LTXAVTEModel_(LTXAVTEModel):
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def __init__(self, device="cpu", dtype=None, model_options={}):
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if llama_scaled_fp8 is not None and "llama_scaled_fp8" not in model_options:
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if llama_quantization_metadata is not None:
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model_options = model_options.copy()
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model_options["llama_scaled_fp8"] = llama_scaled_fp8
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model_options["llama_quantization_metadata"] = llama_quantization_metadata
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if dtype_llama is not None:
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dtype = dtype_llama
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super().__init__(dtype_llama=dtype_llama, device=device, dtype=dtype, model_options=model_options)
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@ -1,3 +1,3 @@
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# This file is automatically generated by the build process when version is
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# updated in pyproject.toml.
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__version__ = "0.7.0"
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__version__ = "0.8.0"
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@ -1,6 +1,6 @@
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[project]
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name = "ComfyUI"
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version = "0.7.0"
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version = "0.8.0"
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readme = "README.md"
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license = { file = "LICENSE" }
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requires-python = ">=3.10"
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