update cuda version in replicate docker image

README.md

@@ -6,7 +6,7 @@
  
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-This is a fast, minimal implementation of Boris Dayma's [DALL·E Mega](https://github.com/borisdayma/dalle-mini).  It has been stripped down for inference and converted to PyTorch.  The only third party dependencies are numpy, requests, pillow and torch.
+This is a fast, minimal port of Boris Dayma's [DALL·E Mega](https://github.com/borisdayma/dalle-mini).  It has been stripped down for inference and converted to PyTorch.  The only third party dependencies are numpy, requests, pillow and torch.
 
 To generate a 4x4 grid of DALL·E Mega images it takes:
 - 89 sec with a T4 in Colab

cog.yaml

@@ -1,13 +1,13 @@
 build:
-  cuda: "11.0"
+  cuda: "11.5.1"
   gpu: true
-  python_version: "3.8"
+  python_version: "3.10"
   system_packages:
     - "libgl1-mesa-glx"
     - "libglib2.0-0"
   python_packages:
     - "min-dalle==0.2.27"
   run:
-    - pip install torch==1.10.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html
+    - pip install torch==1.12.0+cu116 -f https://download.pytorch.org/whl/torch_stable.html
 
 predict: "replicate_predictor.py:ReplicatePredictor"

image_from_text.py

@@ -1,7 +1,6 @@
 import argparse
 import os
 from PIL import Image
-from matplotlib.pyplot import grid
 from min_dalle import MinDalle
 
 

min_dalle.ipynb

@@ -183,7 +183,7 @@
         "text = \"Dali painting of WALL·E\" #@param {type:\"string\"}\n",
         "intermediate_outputs = True #@param {type:\"boolean\"}\n",
         "grid_size = 3 #@param {type:\"integer\"}\n",
-        "supercondition_factor = 8 #@param [\"2\", \"4\", \"8\", \"16\", \"32\", \"64\"] {type:\"raw\"}\n",
+        "supercondition_factor = 16 #@param [\"2\", \"4\", \"8\", \"16\", \"32\", \"64\"] {type:\"raw\"}\n",
         "log2_mid_count = 3 if intermediate_outputs else 0\n",
         "\n",
         "image_stream = model.generate_image_stream(\n",