Update README.md

README.md

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 ---
 library_name: transformers
-tags: []
+tags:
+- Sales
+- FAQ
+- ECommerce
+license: apache-2.0
+language:
+- en
+metrics:
+- accuracy
+pipeline_tag: text-generation
 ---
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
-
+# FAQ Chatbot for Online Orders and Website Queries
 
+This model is a large language model (LLM) based on the LLaMA 3 architecture, fine-tuned to handle frequently asked questions (FAQ) related to online orders and website queries. It is designed to provide accurate and helpful responses to common customer inquiries.
 
 ## Model Details
 
-### Model Description
+- **Model Name:** FAQ Chatbot for Online Orders and Website Queries
+- **Architecture:** LLaMA 3
+- **Training Data:** This model was trained on a dataset consisting of typical customer queries related to online orders, such as order status, payment issues, returns and refunds, shipping information, and general website navigation.
+- **Usage:** The model is intended to be used as a customer support assistant, capable of addressing a wide range of questions about online shopping and website functionality.
+
+## Features
+
+- **Natural Language Understanding:** The model can understand and process natural language input, making it user-friendly for customers.
+- **Contextual Responses:** Provides responses that are contextually relevant to the user's query.
+- **Scalable Support:** Can handle a high volume of queries simultaneously, improving customer service efficiency.
+
+## Example Queries
+
+Here are some example queries that the model can handle:
+
+1. **Order Status:** "Can you tell me the status of my order #12345?"
+2. **Payment Issues:** "I'm having trouble processing my payment. Can you help?"
+3. **Returns and Refunds:** "How can I return a product I bought?"
+4. **Shipping Information:** "When will my order be delivered?"
+5. **Website Navigation:** "How do I find the size chart on your website?"
+
+## How to Use
+
+To use this model, you can integrate it into your customer support system or chatbot framework. Here's a basic example using the Hugging Face `transformers` library:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the model and tokenizer
+model_name = "your-hugging-face-username/faq-chatbot-online-orders"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Example query
+query = "Can you tell me the status of my order #12345?"
+
+# Tokenize the input
+inputs = tokenizer(query, return_tensors="pt")
+
+# Generate response
+outputs = model.generate(**inputs)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print(response)
+
 
-<!-- Provide a longer summary of what this model is. -->
 
 This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
+- **Developed by:** Satwik Kishore
+- **Model type:** Text Generation
+- **Language(s) (NLP):** English
 - **License:** [More Information Needed]
 - **Finetuned from model [optional]:** [More Information Needed]