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--- |
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library_name: transformers |
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tags: |
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- Sales |
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- FAQ |
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- ECommerce |
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license: apache-2.0 |
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language: |
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- en |
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metrics: |
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- accuracy |
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pipeline_tag: text-generation |
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--- |
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# Model Card for Model ID |
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# FAQ Chatbot for Online Orders and Website Queries |
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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. |
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## Model Details |
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- **Model Name:** FAQ Chatbot for Online Orders and Website Queries |
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- **Architecture:** LLaMA 3 |
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- **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. |
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- **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. |
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## Features |
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- **Natural Language Understanding:** The model can understand and process natural language input, making it user-friendly for customers. |
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- **Contextual Responses:** Provides responses that are contextually relevant to the user's query. |
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- **Scalable Support:** Can handle a high volume of queries simultaneously, improving customer service efficiency. |
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## Example Queries |
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Here are some example queries that the model can handle: |
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1. **Order Status:** "Can you tell me the status of my order #12345?" |
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2. **Payment Issues:** "I'm having trouble processing my payment. Can you help?" |
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3. **Returns and Refunds:** "How can I return a product I bought?" |
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4. **Shipping Information:** "When will my order be delivered?" |
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5. **Website Navigation:** "How do I find the size chart on your website?" |
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## How to Use |
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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: |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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# Load the model and tokenizer |
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model_name = "your-hugging-face-username/faq-chatbot-online-orders" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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# Example query |
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query = "Can you tell me the status of my order #12345?" |
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# Tokenize the input |
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inputs = tokenizer(query, return_tensors="pt") |
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# Generate response |
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outputs = model.generate(**inputs) |
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response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print(response) |
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```python |
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
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- **Developed by:** Satwik Kishore |
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- **Model type:** Text Generation |
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- **Language(s) (NLP):** English |
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