fixed up categories

app.py

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+import gradio as gr
+import fastai
+import skimage
+from fastai.vision.all import *
+
+learn=load_learner('model.pkl')
+
+categories=('negative','positive')
+
+def classify(img):
+    pred,idx,probs=learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+
+title = "Text sentiment classifier"
+description = "This model classifies a sentence of text as having a positive or negative setiment"
+text = gr.TextBox()
+label= gr.Label()
+
+intf=gr.Interface(fn=classify,inputs=text,outputs=label,title=title, description=description)
+intf.launch(inline=False)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:94913b9204bae8a28630ad3d28d62dbf2beff010f4c50e52451d53ced36ac879
+size 233513283

requirements.txt

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+fastai==2.7.13
+fastbook==0.0.29
+fastcore==1.5.29
+fastdownload==0.0.7
+fastprogress==1.0.3
+gradio==3.50.0
+graphviz==0.20.1
+ipywidgets==7.7.1
+matplotlib==3.7.4
+numpy==1.24.3
+pandas==2.0.3
+requests==2.31.0
+scipy==1.11.4
+sentencepiece==0.1.99
+session_info==1.0.0
+scikit-learn==1.2.2
+torch==2.0.0
+torchvision==0.15.1
+scikit-image