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https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
chore: flake8
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parent
f6bbcd0589
commit
045d3f6139
@ -350,17 +350,17 @@ class ModelInstall(object):
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for suffix in ["safetensors", "bin"]:
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if f"{prefix}pytorch_lora_weights.{suffix}" in files:
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location = self._download_hf_model(
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repo_id, [f"pytorch_lora_weights.bin"], staging, subfolder=subfolder
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repo_id, ["pytorch_lora_weights.bin"], staging, subfolder=subfolder
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) # LoRA
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break
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elif (
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self.config.precision == "float16" and f"{prefix}diffusion_pytorch_model.fp16.{suffix}" in files
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): # vae, controlnet or some other standalone
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files = [f"config.json", f"diffusion_pytorch_model.fp16.{suffix}"]
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files = ["config.json", f"diffusion_pytorch_model.fp16.{suffix}"]
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location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
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break
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elif f"{prefix}diffusion_pytorch_model.{suffix}" in files:
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files = [f"config.json", f"diffusion_pytorch_model.{suffix}"]
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files = ["config.json", f"diffusion_pytorch_model.{suffix}"]
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location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
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break
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elif f"{prefix}learned_embeds.{suffix}" in files:
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@ -371,13 +371,13 @@ class ModelInstall(object):
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elif (
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f"{prefix}image_encoder.txt" in files and f"{prefix}ip_adapter.{suffix}" in files
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): # IP-Adapter
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files = [f"image_encoder.txt", f"ip_adapter.{suffix}"]
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files = ["image_encoder.txt", f"ip_adapter.{suffix}"]
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location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
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break
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elif f"{prefix}model.{suffix}" in files and f"{prefix}config.json" in files:
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# This elif-condition is pretty fragile, but it is intended to handle CLIP Vision models hosted
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# by InvokeAI for use with IP-Adapters.
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files = [f"config.json", f"model.{suffix}"]
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files = ["config.json", f"model.{suffix}"]
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location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
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break
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if not location:
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