feat(wip): lycoris
Browse files- app.py +55 -29
- requirements.txt +3 -1
app.py
CHANGED
@@ -2,10 +2,13 @@ import torch
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import gradio as gr
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import spaces
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import random
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from diffusers.utils import export_to_video
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from diffusers import AutoencoderKLWan, WanPipeline
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from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepScheduler
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from diffusers.schedulers.scheduling_flow_match_euler_discrete import FlowMatchEulerDiscreteScheduler
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# Define model options
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MODEL_OPTIONS = {
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@@ -19,14 +22,39 @@ SCHEDULER_OPTIONS = {
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"FlowMatchEulerDiscreteScheduler": FlowMatchEulerDiscreteScheduler
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}
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@spaces.GPU(duration=300)
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def generate_video(
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model_choice,
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prompt,
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negative_prompt,
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-
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-
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-
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scheduler_type,
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flow_shift,
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height,
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@@ -65,24 +93,22 @@ def generate_video(
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# Move to GPU
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pipe.to("cuda")
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# Load
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if
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try:
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#
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if
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-
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-
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-
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# Set lora scale if applicable
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if hasattr(pipe, "set_adapters_scale") and lora_scale is not None:
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pipe.set_adapters_scale(lora_scale)
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except ValueError as e:
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# Return informative error if there are
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if "more than one weights file" in str(e):
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return f"Error: The repository '{
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else:
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return f"Error loading
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# Enable CPU offload for low VRAM
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pipe.enable_model_cpu_offload()
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@@ -114,7 +140,7 @@ with gr.Blocks() as demo:
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</svg>
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</p>
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""")
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gr.Markdown("# Wan 2.1 T2V
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with gr.Row():
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with gr.Column(scale=1):
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@@ -137,19 +163,19 @@ with gr.Blocks() as demo:
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)
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with gr.Row():
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-
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label="
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value="TheBulge/AndroWan-2.1-T2V-1.3B"
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)
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with gr.Row():
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-
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label="
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value="safetensors/AndroWan_v32-0036_ema.safetensors",
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info="Specify for repos with multiple .safetensors files, e.g.: adapter_model.safetensors, pytorch_lora_weights.safetensors, etc."
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)
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-
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label="
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minimum=0.0,
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maximum=2.0,
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value=1.00,
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@@ -238,9 +264,9 @@ with gr.Blocks() as demo:
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model_choice,
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prompt,
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negative_prompt,
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-
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-
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-
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scheduler_type,
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flow_shift,
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height,
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- Number of frames should be of the form 4k+1 (e.g., 33, 81)
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- Stick to lower frame counts. Even at 480p, an 81 frame sequence at 30 steps will nearly time out the request in this space.
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## Using
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If you encounter an error stating "
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You can find this by browsing the repository on Hugging Face and looking for the safetensors files (common names include: adapter_model.safetensors, pytorch_lora_weights.safetensors).
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""")
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import gradio as gr
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import spaces
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import random
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import os
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from diffusers.utils import export_to_video
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from diffusers import AutoencoderKLWan, WanPipeline
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from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepScheduler
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from diffusers.schedulers.scheduling_flow_match_euler_discrete import FlowMatchEulerDiscreteScheduler
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from huggingface_hub import hf_hub_download
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from lycoris import create_lycoris_from_weights
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# Define model options
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MODEL_OPTIONS = {
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"FlowMatchEulerDiscreteScheduler": FlowMatchEulerDiscreteScheduler
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}
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def download_adapter(repo_id, weight_name=None):
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"""
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Download the adapter file from the Hugging Face Hub.
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If weight_name is not provided, attempts to use pytorch_lora_weights.safetensors
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"""
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adapter_filename = weight_name if weight_name else "pytorch_lora_weights.safetensors"
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cache_dir = os.environ.get('HF_PATH', os.path.expanduser('~/.cache/huggingface/hub/models'))
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cleaned_adapter_path = repo_id.replace("/", "_").replace("\\", "_").replace(":", "_")
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path_to_adapter = os.path.join(cache_dir, cleaned_adapter_path)
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os.makedirs(path_to_adapter, exist_ok=True)
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try:
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path_to_adapter_file = hf_hub_download(
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repo_id=repo_id,
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filename=adapter_filename,
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local_dir=path_to_adapter
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)
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return path_to_adapter_file
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except Exception as e:
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# If specific file not found, try to get a list of available safetensors files
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if weight_name is None:
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raise ValueError(f"Could not download default adapter file: {str(e)}\nPlease specify the exact weight file name.")
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else:
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raise ValueError(f"Could not download adapter file {weight_name}: {str(e)}")
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@spaces.GPU(duration=300)
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def generate_video(
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model_choice,
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prompt,
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negative_prompt,
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lycoris_id,
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lycoris_weight_name,
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lycoris_scale,
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scheduler_type,
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flow_shift,
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height,
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# Move to GPU
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pipe.to("cuda")
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# Load LyCORIS weights if provided
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if lycoris_id and lycoris_id.strip():
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try:
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# Download the adapter file
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adapter_file_path = download_adapter(repo_id=lycoris_id, weight_name=lycoris_weight_name if lycoris_weight_name and lycoris_weight_name.strip() else None)
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# Apply LyCORIS adapter
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wrapper, *_ = create_lycoris_from_weights(lycoris_scale, adapter_file_path, pipe.transformer)
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wrapper.merge_to()
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except ValueError as e:
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# Return informative error if there are issues loading the adapter
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if "more than one weights file" in str(e) or "Could not download default adapter file" in str(e):
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return f"Error: The repository '{lycoris_id}' may contain multiple weight files. Please specify a weight name using the 'LyCORIS Weight Name' field.", seed
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else:
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return f"Error loading LyCORIS weights: {str(e)}", seed
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# Enable CPU offload for low VRAM
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pipe.enable_model_cpu_offload()
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</svg>
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</p>
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""")
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gr.Markdown("# Wan 2.1 T2V with LyCORIS")
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with gr.Row():
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with gr.Column(scale=1):
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)
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with gr.Row():
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lycoris_id = gr.Textbox(
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label="LyCORIS Model Repo (e.g., TheBulge/AndroWan-2.1-T2V-1.3B)",
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value="TheBulge/AndroWan-2.1-T2V-1.3B"
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)
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with gr.Row():
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lycoris_weight_name = gr.Textbox(
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label="LyCORIS Weight Path in Repo (optional)",
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value="safetensors/AndroWan_v32-0036_ema.safetensors",
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info="Specify for repos with multiple .safetensors files, e.g.: adapter_model.safetensors, pytorch_lora_weights.safetensors, etc."
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)
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lycoris_scale = gr.Slider(
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label="LyCORIS Scale",
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minimum=0.0,
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maximum=2.0,
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value=1.00,
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model_choice,
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prompt,
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negative_prompt,
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lycoris_id,
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lycoris_weight_name,
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lycoris_scale,
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scheduler_type,
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flow_shift,
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height,
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- Number of frames should be of the form 4k+1 (e.g., 33, 81)
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- Stick to lower frame counts. Even at 480p, an 81 frame sequence at 30 steps will nearly time out the request in this space.
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+
## Using LyCORIS with multiple safetensors files:
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If you encounter an error stating "Could not download default adapter file", you need to specify the exact weight file name in the "LyCORIS Weight Name" field.
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You can find this by browsing the repository on Hugging Face and looking for the safetensors files (common names include: adapter_model.safetensors, pytorch_lora_weights.safetensors).
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""")
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requirements.txt
CHANGED
@@ -7,4 +7,6 @@ ftfy>=6.1.3
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einops>=0.7.0
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imageio>=2.31.6
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imageio-ffmpeg>=0.4.9
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-
peft==0.7.1
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einops>=0.7.0
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imageio>=2.31.6
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imageio-ffmpeg>=0.4.9
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peft==0.7.1
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lycoris-lora>=0.1.5
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huggingface_hub>=0.19.0
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