go

Dockerfile

@@ -1,7 +1,9 @@
 # read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
 # you will also find guides on how best to write your Dockerfile
 
-FROM python:3.9
+FROM dnxie/resym
+
+RUN git clone https://github.com/lt-asset/resym /home/ReSym
 
 WORKDIR /code
 

main.py

@@ -1,26 +1,14 @@
 import gradio as gr
-import torch
-import requests
-from torchvision import transforms
-
-model = torch.hub.load("pytorch/vision:v0.6.0", "resnet18", pretrained=True).eval()
-response = requests.get("https://git.io/JJkYN")
-labels = response.text.split("\n")
-
 
 def predict(inp):
-    inp = transforms.ToTensor()(inp).unsqueeze(0)
-    with torch.no_grad():
-        prediction = torch.nn.functional.softmax(model(inp)[0], dim=0)
-        confidences = {labels[i]: float(prediction[i]) for i in range(1000)}
-    return confidences
+    return "Hi"
 
 
 def run():
     demo = gr.Interface(
         fn=predict,
-        inputs=gr.Image(type="pil"),
-        outputs=gr.Label(num_top_classes=3),
+        inputs=gr.Text,
+        outputs=gr.Text,
     )
 
     demo.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

@@ -1,4 +1 @@
 gradio
-torch
-torchvision
-requests