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._decision_tree_regressor.joblib

@@ -1,3 +1,3 @@
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 size 4096

.idea/workspace.xml

@@ -4,7 +4,7 @@
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   </component>
   <component name="ChangeListManager">
-    <list default="true" id="110c2627-9032-47cf-a1c1-bc62c4ddc737" name="Changes" comment="" />
+    <list default="true" id="110c2627-9032-47cf-a1c1-bc62c4ddc737" name="Changes" comment="alpha 0.1" />
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@@ -56,6 +56,19 @@
       <option name="presentableId" value="Default" />
       <updated>1699914106482</updated>
     </task>
+    <task id="LOCAL-00001" summary="alpha 0.1">
+      <option name="closed" value="true" />
+      <created>1699947245832</created>
+      <option name="number" value="00001" />
+      <option name="presentableId" value="LOCAL-00001" />
+      <option name="project" value="LOCAL" />
+      <updated>1699947245832</updated>
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+    <option name="localTasksCounter" value="2" />
     <servers />
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+  <component name="VcsManagerConfiguration">
+    <MESSAGE value="alpha 0.1" />
+    <option name="LAST_COMMIT_MESSAGE" value="alpha 0.1" />
+  </component>
 </project>

app.py

@@ -1,8 +1,9 @@
 import gradio as gr
 import pandas as pd
 import joblib
-from gpt4all import GPT4Allt
+from gpt4all import GPT4All
 from sklearn.tree import DecisionTreeRegressor
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Load the trained model
 decision_tree_regressor = joblib.load('./decision_tree_regressor.joblib')
@@ -11,7 +12,6 @@ decision_tree_regressor = joblib.load('./decision_tree_regressor.joblib')
 model_name = "mistral-7b-openorca.Q4_0.gguf"  # Replace with your preferred model
 model = GPT4All(model_name)
 
-
 def collect_data(fasting_duration, meal_timing, body_weight, age, gender, height):
     # Prepare the data for prediction
     data = {

decision_tree_regressor.joblib

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requirements.txt

@@ -2,4 +2,7 @@ joblib~=1.2.0
 gpt4all~=2.0.2
 gradio
 pandas
-scikit-learn
+scikit-learn==1.3.1
+huggingface-hub
+transformers
+charset_normalizer