adding pickle

app.py

@@ -2,7 +2,6 @@ import numpy as np
 import os
 import gradio as gr
 import xgboost as xgb
-import pickle
 from sklearn.feature_extraction.text import TfidfVectorizer
 
 os.environ["WANDB_DISABLED"] = "true"
@@ -10,12 +9,11 @@ os.environ["WANDB_DISABLED"] = "true"
 label2id =  {
     0: "negative",
     1: "neutral",
-    2: "positive",
-    3: "mixed"
+    2: "positive"
   }
 
-model_file_name = "svc_model.pkl"
-vectorizer_file_name = 'vectorizer.pkl'
+model_file_name = "xgb_reg.pkl"
+vectorizer_file_name = 'vectorizer.pk'
 
 #load
 xgb_model_loaded = pickle.load(open(model_file_name, "rb"))

requirements.txt

@@ -1,4 +1,4 @@
 gradio
 xgboost
-scikit-learn==1.5
+scikit-learn
 pandas

svc_model.pkl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f9a157abb60761327ed18ef8345c06df0ac62fd877eeb76c021d3bd83df41b6e
-size 675470

vectorizer.pkl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3ef1996721215dd7831612b4ca9e29d63a2da66f13ec93d6067b8df8756fece7
-size 231609