Upload Screenshot 2023-04-05 at 6.25.06 PM.png

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Screenshot[[:space:]]2023-04-05[[:space:]]at[[:space:]]6.25.06[[:space:]]PM.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -119,6 +119,7 @@ with gr.Blocks() as demo:
     gr.Markdown("<h1><center>HuggingGPT</center></h1>")
     gr.Markdown("<p align='center'><img src='https://i.ibb.co/qNH3Jym/logo.png' height='25' width='95'></p>")
     gr.Markdown("<p align='center' style='font-size: 20px;'>A system to connect LLMs with ML community. See our <a href='https://github.com/microsoft/JARVIS'>Project</a> and <a href='http://arxiv.org/abs/2303.17580'>Paper</a>.</p>")
+    gr.HTML('''<center><a href="https://huggingface.co/spaces/microsoft/HuggingGPT?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key and Hugging Face Token</center>''')
     with gr.Row().style():
         with gr.Column(scale=0.85):
             openai_api_key = gr.Textbox(

models_server.py

@@ -162,10 +162,10 @@ def load_pipes(local_deployment):
             #     "tokenizer": AutoTokenizer.from_pretrained(f"{local_models}nlpconnect/vit-gpt2-image-captioning"),
             #     "device": "cuda:0"
             # },
-            # "espnet/kan-bayashi_ljspeech_vits": {
-            #     "model": Text2Speech.from_pretrained("espnet/kan-bayashi_ljspeech_vits"),
-            #     "device": "cuda:0"
-            # },
+            "espnet/kan-bayashi_ljspeech_vits": {
+                "model": Text2Speech.from_pretrained("espnet/kan-bayashi_ljspeech_vits"),
+                "device": "cuda:0"
+            },
             # "lambdalabs/sd-image-variations-diffusers": {
             #     "model": DiffusionPipeline.from_pretrained(f"{local_models}lambdalabs/sd-image-variations-diffusers"), #torch_dtype=torch.float16
             #     "device": "cuda:0"