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Browse files- app-fast.py +10 -11
- pyproject.toml +1 -0
- requirements.txt +1 -1
- uv.lock +11 -615
app-fast.py
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@@ -2,20 +2,23 @@ import gradio as gr
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import PIL
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import spaces
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import torch
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from diffusers import TorchAoConfig
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from hi_diffusers import HiDreamImagePipeline, HiDreamImageTransformer2DModel
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from hi_diffusers.schedulers.flash_flow_match import (
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FlashFlowMatchEulerDiscreteScheduler,
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)
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from transformers import (
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AutoModelForCausalLM,
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AutoTokenizer,
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-
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)
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# Constants
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MODEL_PREFIX: str = "HiDream-ai"
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LLAMA_MODEL_NAME: str = "
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MODEL_PATH = "HiDream-ai/HiDream-I1-Fast"
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MODEL_CONFIGS = {
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"guidance_scale": 0.0,
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@@ -37,11 +40,9 @@ RESOLUTION_OPTIONS: list[str] = [
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]
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do_fuse=True,
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)
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tokenizer = AutoTokenizer.from_pretrained(LLAMA_MODEL_NAME, use_fast=False)
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text_encoder = AutoModelForCausalLM.from_pretrained(
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@@ -54,9 +55,7 @@ text_encoder = AutoModelForCausalLM.from_pretrained(
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quantization_config=quantization_config,
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).to("cuda")
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quantization_config =
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-
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quantization_config = TorchAoConfig("int8wo")
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transformer = HiDreamImageTransformer2DModel.from_pretrained(
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MODEL_PATH,
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subfolder="transformer",
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import PIL
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import spaces
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import torch
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from diffusers import TorchAoConfig as DiffusersTorchAoConfig
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from hi_diffusers import HiDreamImagePipeline, HiDreamImageTransformer2DModel
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from hi_diffusers.schedulers.flash_flow_match import (
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FlashFlowMatchEulerDiscreteScheduler,
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)
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from torchao.quantization import Int4WeightOnlyConfig
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from transformers import (
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AutoModelForCausalLM,
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AutoTokenizer,
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)
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from transformers import (
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TorchAoConfig as TransformersTorchAoConfig,
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)
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# Constants
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MODEL_PREFIX: str = "HiDream-ai"
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LLAMA_MODEL_NAME: str = "meta-llama/Meta-Llama-3.1-8B-Instruct"
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MODEL_PATH = "HiDream-ai/HiDream-I1-Fast"
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MODEL_CONFIGS = {
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"guidance_scale": 0.0,
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]
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# Using AOBaseConfig instance (torchao >= 0.10.0)
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quant_config = Int4WeightOnlyConfig(group_size=128)
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quantization_config = TransformersTorchAoConfig(quant_type=quant_config)
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tokenizer = AutoTokenizer.from_pretrained(LLAMA_MODEL_NAME, use_fast=False)
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text_encoder = AutoModelForCausalLM.from_pretrained(
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quantization_config=quantization_config,
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).to("cuda")
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quantization_config = DiffusersTorchAoConfig("int8wo")
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transformer = HiDreamImageTransformer2DModel.from_pretrained(
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MODEL_PATH,
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subfolder="transformer",
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pyproject.toml
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@@ -9,6 +9,7 @@ dependencies = [
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"diffusers>=0.32.1",
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"einops>=0.7.0",
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"torch>=2.5.1",
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"torchvision>=0.20.1",
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"transformers>=4.47.1",
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]
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"diffusers>=0.32.1",
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"einops>=0.7.0",
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"torch>=2.5.1",
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"torchao>=0.10.0",
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"torchvision>=0.20.1",
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"transformers>=4.47.1",
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]
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requirements.txt
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@@ -10,4 +10,4 @@ einops
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gradio
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spaces
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sentencepiece
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gradio
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spaces
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sentencepiece
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torchao
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uv.lock
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| 731 |
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| 732 |
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| 733 |
[[package]]
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| 734 |
name = "typing-extensions"
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| 735 |
version = "4.13.1"
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| 739 |
{ url = "https://files.pythonhosted.org/packages/df/c5/e7a0b0f5ed69f94c8ab7379c599e6036886bffcde609969a5325f47f1332/typing_extensions-4.13.1-py3-none-any.whl", hash = "sha256:4b6cf02909eb5495cfbc3f6e8fd49217e6cc7944e145cdda8caa3734777f9e69", size = 45739 },
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| 740 |
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| 741 |
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| 742 |
[[package]]
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| 743 |
name = "urllib3"
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| 744 |
version = "2.3.0"
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| 748 |
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| 749 |
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| 750 |
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| 751 |
[[package]]
|
| 752 |
name = "zipp"
|
| 753 |
version = "3.21.0"
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