feat: model, app, requirements

app.py

@@ -0,0 +1,57 @@
+import gradio as gr
+import torch
+from torch import tensor
+from torch.nn import functional as F
+from sklearn.preprocessing import LabelEncoder
+import pandas as pd
+
+label_encoder = LabelEncoder()
+
+coeffs = torch.load('fakejobposts.pth')
+
+indep_cols = ['job_title', 'company_name', 'company_desc', 'job_desc',
+              'job_requirement', 'salary', 'location', 'employment_type',
+              'department']
+
+def calc_preds(coeffs, indeps):
+    layers, consts = coeffs
+    n = len(layers)
+    res = indeps
+    for i, l in enumerate(layers):
+        res = res @ l + consts[i]
+        if i != n-1:
+            res = F.relu(res)
+    if torch.sigmoid(res) > 0.5:
+        return 'Real Job Post'
+    else:
+        return 'Fake Job Post'
+
+def main(job_title, company_name, company_desc, job_desc,
+              job_requirement, salary, location, employment_type,
+              department):
+    df = pd.DataFrame(columns=indep_cols)
+    df.loc[0] = [job_title, company_name, company_desc, job_desc,
+              job_requirement, salary, location, employment_type,
+              department]
+
+    for column in df.columns:
+        df[column] = label_encoder.fit_transform(df[column])
+
+    t_indep = tensor(df[indep_cols].values, dtype=torch.float)
+    vals,indices = t_indep.max(dim=0)
+    t_indep = t_indep / vals
+    return calc_preds(coeffs, t_indep)
+
+iface = gr.Interface(
+    fn=main,
+    inputs=[gr.Textbox(label="Job title"), gr.Textbox(label="Company name"),
+            gr.Textbox(label="Company description"), gr.Textbox(label="Job description"),
+            gr.Textbox(label="Job Requirements"), gr.Textbox(label="Salary"),
+            gr.Textbox(label="Location"), gr.Textbox(label="Employment Type"),
+            gr.Textbox(label="Department")],
+    outputs="text",
+    title="Job posting identifier",
+    description="Identifies job posts as real or fake"
+)
+
+iface.launch()

fakejobposts.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ef267d4b182c048a7a82f4ebe7c4c1496780a7a0d5da802411d9046eba0e65aa
+size 2687

requirements.txt

@@ -0,0 +1 @@
+fastai