diff --git a/webui.py b/webui.py
index 51ce02c7e..55654f559 100644
--- a/webui.py
+++ b/webui.py
@@ -58,6 +58,7 @@ parser.add_argument("--grid-extended-filename",  action='store_true', help="save
 parser.add_argument("--jpeg-quality", type=int, default=80, help="quality for saved jpeg images")
 parser.add_argument("--disable-pnginfo", action='store_true', help="disable saving text information about generation parameters as chunks to png files")
 
+parser.add_argument("--inversion", action='store_true', help="switch to stable inversion version; allows for uploading embeddings; this option should be used only with textual inversion repo")
 opt = parser.parse_args()
 
 GFPGAN_dir = opt.gfpgan_dir
@@ -189,8 +190,8 @@ if os.path.exists(GFPGAN_dir):
         print("Error loading GFPGAN:", file=sys.stderr)
         print(traceback.format_exc(), file=sys.stderr)
 
-config = OmegaConf.load("configs/stable-diffusion/v1-inference.yaml")
-model = load_model_from_config(config, "models/ldm/stable-diffusion-v1/model.ckpt")
+config = OmegaConf.load(opt.config)
+model = load_model_from_config(config, opt.ckpt)
 
 device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
 model = (model if opt.no_half else model.half()).to(device)
@@ -467,9 +468,17 @@ def process_images(outpath, func_init, func_sample, prompt, seed, sampler_name,
     return output_images, seed, info
 
 
-def txt2img(prompt: str, ddim_steps: int, sampler_name: str, use_GFPGAN: bool, prompt_matrix: bool, ddim_eta: float, n_iter: int, batch_size: int, cfg_scale: float, seed: int, height: int, width: int):
+def load_embeddings(fp):
+    if fp is not None and hasattr(model, "embedding_manager"):
+    # load the file
+        model.embedding_manager.load(fp.name)
+    
+
+def txt2img(prompt: str, ddim_steps: int, sampler_name: str, use_GFPGAN: bool, prompt_matrix: bool, ddim_eta: float, n_iter: int, batch_size: int, cfg_scale: float, seed: int, height: int, width: int, embeddings_fp):
     outpath = opt.outdir or "outputs/txt2img-samples"
 
+    load_embeddings(embeddings_fp)
+
     if sampler_name == 'PLMS':
         sampler = PLMSSampler(model)
     elif sampler_name == 'DDIM':
@@ -564,6 +573,7 @@ txt2img_interface = gr.Interface(
         gr.Number(label='Seed', value=-1),
         gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512),
         gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512),
+        gr.File(label = "Embeddings file for textual inversion", visible=opt.inversion)
     ],
     outputs=[
         gr.Gallery(label="Images"),
@@ -576,9 +586,11 @@ txt2img_interface = gr.Interface(
 )
 
 
-def img2img(prompt: str, init_img, ddim_steps: int, use_GFPGAN: bool, prompt_matrix, loopback: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, height: int, width: int, resize_mode: int):
+def img2img(prompt: str, init_img, ddim_steps: int, use_GFPGAN: bool, prompt_matrix, loopback: bool, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, height: int, width: int, resize_mode: int, embeddings_fp):
     outpath = opt.outdir or "outputs/img2img-samples"
 
+    load_embeddings(embeddings_fp)
+
     sampler = KDiffusionSampler(model)
 
     assert 0. <= denoising_strength <= 1., 'can only work with strength in [0.0, 1.0]'
@@ -693,7 +705,8 @@ img2img_interface = gr.Interface(
         gr.Number(label='Seed', value=-1),
         gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512),
         gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512),
-        gr.Radio(label="Resize mode", choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize")
+        gr.Radio(label="Resize mode", choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize"),
+        gr.File(label = "Embeddings file for textual inversion", visible=opt.inversion)
     ],
     outputs=[
         gr.Gallery(),
@@ -739,6 +752,7 @@ if GFPGAN is not None:
         allow_flagging="never",
     ), "GFPGAN"))
 
+
 demo = gr.TabbedInterface(
     interface_list=[x[0] for x in interfaces],
     tab_names=[x[1] for x in interfaces],
@@ -748,4 +762,4 @@ demo = gr.TabbedInterface(
 """
 )
 
-demo.launch()
+demo.launch()
\ No newline at end of file