Add requirements.txt

.ipynb_checkpoints/app-checkpoint.py

@@ -1,4 +1,5 @@
 import streamlit as st
+import torch
 from huggingface_hub import model_info
 from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
 
@@ -6,7 +7,7 @@ def inference(prompt, model, n_images, seed):
     # Load the model
     info = model_info(model)
     model_base = info.cardData["base_model"]
-    pipe = StableDiffusionPipeline.from_pretrained(model_base)
+    pipe = StableDiffusionPipeline.from_pretrained(model_base, torch_dtype=torch.float32)
     pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
 
     pipe.unet.load_attn_procs(model)

.ipynb_checkpoints/requirements-checkpoint.txt

@@ -0,0 +1,5 @@
+transformers
+diffusers
+huggingface_hub
+streamlit
+torch

app.py

@@ -1,4 +1,5 @@
 import streamlit as st
+import torch
 from huggingface_hub import model_info
 from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
 
@@ -6,7 +7,7 @@ def inference(prompt, model, n_images, seed):
     # Load the model
     info = model_info(model)
     model_base = info.cardData["base_model"]
-    pipe = StableDiffusionPipeline.from_pretrained(model_base)
+    pipe = StableDiffusionPipeline.from_pretrained(model_base, torch_dtype=torch.float32)
     pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
 
     pipe.unet.load_attn_procs(model)

requirements.txt

@@ -0,0 +1,5 @@
+transformers
+diffusers
+huggingface_hub
+streamlit
+torch