Update app.py

app.py

@@ -1,32 +1,32 @@
 import gradio as gr
 
-#gr.Interface.load("models/nitinbhayana/Llama-2-7b-chat-hf-keyword-category-brand-v1").launch()
+gr.Interface.load("models/nitinbhayana/Llama-2-7b-chat-hf-keyword-category-brand-v1").launch()
 
 
-from transformers import pipeline
+# from transformers import pipeline
 
-pipeline = pipeline("text-generation", model="nitinbhayana/Llama-2-7b-chat-hf-keyword-category-brand-v1")
+# pipeline = pipeline("text-generation", model="nitinbhayana/Llama-2-7b-chat-hf-keyword-category-brand-v1")
 
-def predict(search_term):
+# def predict(search_term):
     
-    prompt=f"""[INST] <<SYS>>
-You are a helpful assistant that provides accurate and concise responses. Do not hallucinate.
-<</SYS>>
-Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
-### Instruction:
-Analyze the following keyword searched on amazon with intent of shopping. Identify the product category from the list ['Baby Products', 'Bags, Wallets and Luggage', 'Beauty', 'Books', 'Car & Motorbike', 'Clothing & Accessories', 'Computers & Accessories', 'Electronics', 'Garden & Outdoors', 'Gift Cards', 'Grocery & Gourmet Foods', 'Health & Personal Care', 'Home & Kitchen', 'Home Improvement', 'Industrial & Scientific', 'Jewellery', 'Kindle Store', 'Movies & TV Shows', 'Music', 'Musical Instruments', 'Office Products', 'Pet Supplies', 'Shoes & Handbags', 'Software', 'Sports, Fitness & Outdoors', 'Toys & Games', 'Video Games', 'Watches']. Extract the brand from keyword related to brand loyalty intent.\nOutput in JSON with keyword, product category, brand as keys.
-### Input:
-{search_term}
-[/INST]"""
-    predictions = pipeline(prompt)
-    return (predictions)
-
-gr.Interface(
-    predict,
-    inputs='text',
-    outputs='text',
-    title="Keyword-Category-Brand-Mapping",
-).launch()
+#     prompt=f"""[INST] <<SYS>>
+# You are a helpful assistant that provides accurate and concise responses. Do not hallucinate.
+# <</SYS>>
+# Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+# ### Instruction:
+# Analyze the following keyword searched on amazon with intent of shopping. Identify the product category from the list ['Baby Products', 'Bags, Wallets and Luggage', 'Beauty', 'Books', 'Car & Motorbike', 'Clothing & Accessories', 'Computers & Accessories', 'Electronics', 'Garden & Outdoors', 'Gift Cards', 'Grocery & Gourmet Foods', 'Health & Personal Care', 'Home & Kitchen', 'Home Improvement', 'Industrial & Scientific', 'Jewellery', 'Kindle Store', 'Movies & TV Shows', 'Music', 'Musical Instruments', 'Office Products', 'Pet Supplies', 'Shoes & Handbags', 'Software', 'Sports, Fitness & Outdoors', 'Toys & Games', 'Video Games', 'Watches']. Extract the brand from keyword related to brand loyalty intent.\nOutput in JSON with keyword, product category, brand as keys.
+# ### Input:
+# {search_term}
+# [/INST]"""
+#     predictions = pipeline(prompt)
+#     return (predictions)
+
+# gr.Interface(
+#     predict,
+#     inputs='text',
+#     outputs='text',
+#     title="Keyword-Category-Brand-Mapping",
+# ).launch()