sd model no more need hf_access_token

scripts/README.md

@@ -1,11 +1,9 @@
 # Lama Cleaner One Click Installer
 
-
 ## Model Description
 
 - **lama**: State of the art image inpainting AI model, useful to remove any unwanted object, defect, people from your pictures.
-- **sd1.5**: Stable Diffusion model, text-driven image editing. To use this model you need to [accepting the terms to access](https://huggingface.co/runwayml/stable-diffusion-inpainting), and
-  get an access token from here [huggingface access token](https://huggingface.co/docs/hub/security-tokens).
+- **sd1.5**: Stable Diffusion model, text-driven image editing.
 
 ## Windows
 
@@ -14,7 +12,6 @@
 1. Double click `win_config.bat`, follow the guide in the terminal to choice [model](#model-description) and set other configs.
 1. Double click `win_start.bat` to start the server.
 
-
 ## Q&A
 
 **How to update the version?**
@@ -24,6 +21,7 @@ Rerun `win_config.bat` will install the newest version of lama-cleaner
 **Where is model downloaded?**
 
 By default, model will be downloaded to user folder
+
 - stable diffusion model: `C:\Users\your_name\.cache\huggingface`
 - lama model: `C:\Users\your_name\.cache\torch`
 
@@ -36,4 +34,3 @@ set TORCH_HOME=your_directory
 set HF_HOME=your_directory
 @call invoke start
 ```
-

scripts/user_scripts/tasks.py

@@ -31,6 +31,7 @@ CONFIG_PATH = "config.json"
 class MODEL(str, Enum):
     SD15 = "sd1.5"
     LAMA = "lama"
+    PAINT_BY_EXAMPLE = 'paint_by_example'
 
 
 class DEVICE(str, Enum):
@@ -48,7 +49,7 @@ def info(c):
         c.run("python --version")
         c.run("which pip")
         c.run("pip --version")
-        c.run('pip list | grep "torch\|lama\|diffusers\|opencv\|cuda"')
+        c.run('pip list | grep "torch\|lama\|diffusers\|opencv\|cuda\|xformers\|accelerate"')
     except:
         pass
     print("-" * 60)
@@ -56,23 +57,10 @@ def info(c):
 
 @task(pre=[info])
 def config(c, disable_device_choice=False):
-    # TODO: 提示选择模型，选择设备，端口，host
-    # 如果是 sd 模型，提示接受条款和输入 huggingface token
     model = Prompt.ask(
-        "Choice model", choices=[MODEL.SD15, MODEL.LAMA], default=MODEL.SD15
+        "Choice model", choices=[MODEL.SD15, MODEL.LAMA, MODEL.PAINT_BY_EXAMPLE], default=MODEL.SD15
     )
 
-    hf_access_token = ""
-    if model == MODEL.SD15:
-        while True:
-            hf_access_token = Prompt.ask(
-                "Huggingface access token (https://huggingface.co/docs/hub/security-tokens)"
-            )
-            if hf_access_token == "":
-                log.warning("Access token is required to download model")
-            else:
-                break
-
     if disable_device_choice:
         device = DEVICE.CPU
     else:
@@ -93,7 +81,6 @@ def config(c, disable_device_choice=False):
     configs = {
         "model": model,
         "device": device,
-        "hf_access_token": hf_access_token,
         "desktop": desktop,
     }
     log.info(f"Save config to {CONFIG_PATH}")
@@ -114,17 +101,16 @@ def start(c):
 
     model = configs["model"]
     device = configs["device"]
-    hf_access_token = configs["hf_access_token"]
     desktop = configs["desktop"]
     port = find_free_port()
     log.info(f"Using random port: {port}")
 
     if desktop:
         c.run(
-            f"lama-cleaner --model {model} --device {device} --hf_access_token={hf_access_token} --port {port} --gui --gui-size 1400 900"
+            f"lama-cleaner --model {model} --device {device} --port {port} --gui --gui-size 1400 900"
         )
     else:
         c.run(
-            f"lama-cleaner --model {model} --device {device} --hf_access_token={hf_access_token} --port {port}"
+            f"lama-cleaner --model {model} --device {device} --port {port}"
         )