abhinav-chatbot

Abhinav Academy Chatbot

A fine-tuned language model designed to answer questions about Abhinav Academy's courses, facilities, and services. This model is based on EleutherAI's GPT-Neo 1.3B and has been specifically trained to provide accurate information about the institution.

Model Details

• Base Model: EleutherAI/gpt-neo-1.3B
• Training Dataset: Custom dataset of question-answer pairs about Abhinav Academy
• Task: Instruction-following for educational institution information
• Primary Use Case: Answering student and parent queries about Abhinav Academy

Use Cases

This model is designed to:

• Answer questions about course offerings (JEE, NEET, MHT-CET preparation)
• Provide information about faculty and facilities
• Explain admission requirements and processes
• Share details about extracurricular activities
• Address queries about fees, scholarships, and logistical details

Example Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

# Load model and tokenizer
model_name = "accesscreate012/abhinav-chatbot"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Function to generate responses
def generate_response(instruction, max_new_tokens=150):
    prompt = f"Instruction: {instruction}\nResponse:"
    
    # Tokenize the input
    inputs = tokenizer(prompt, return_tensors="pt")
    
    # Generate with improved parameters
    outputs = model.generate(
        **inputs,
        max_new_tokens=max_new_tokens,
        num_beams=5,
        no_repeat_ngram_size=3,
        early_stopping=True,
        top_p=0.92,
        temperature=0.7,
        do_sample=True,
        pad_token_id=tokenizer.eos_token_id
    )
    
    # Process and clean the output
    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    
    # Extract only the response part
    if "Response:" in generated_text:
        response = generated_text.split("Response:")[1].strip()
    else:
        response = generated_text.replace(prompt, "").strip()
    
    return response

# Example queries
queries = [
    "What courses do you offer for JEE preparation?",
    "Tell me about your NEET coaching program",
    "Where is Abhinav Academy located?",
    "Do you have hostel facilities?"
]

# Generate and print responses
for query in queries:
    print(f"Q: {query}")
    print(f"A: {generate_response(query)}")
    print()

Sample Interactions

Q: What courses does Abhinav Academy offer?
A: We offer MHT-CET, JEE, NEET preparation, as well as supplementary courses like English Communication, Personality Development, and Foreign Languages (German/French).

Q: Does Abhinav Academy offer NEET coaching?
A: Yes, we offer NEET coaching with expert faculty and structured study materials. Our 24-month NEET Preparation program emphasizes NCERT-based learning and practical lab sessions for Biology, Physics, and Chemistry.

Q: What are the admission requirements for Abhinav Academy?
A: Admission requirements vary by program. Generally, students must pass an entrance test and interview. Competitive courses require strong academics.

Limitations

• The model is specialized for information about Abhinav Academy only
• It may not provide accurate information about other educational institutions
• Responses are based on training data and may not reflect real-time changes to curriculum or policies
• The model should be regularly updated as the institution's offerings evolve

Training Methodology

This model was fine-tuned using a supervised approach on a custom dataset containing question-answer pairs about Abhinav Academy. The training process focused on:

• Preserving factual accuracy about course offerings
• Maintaining consistent formatting and tone
• Optimizing for natural-sounding responses
• Handling variations in question phrasing

Integration

This model can be integrated into:

• The academy's official website as a chat assistant
• Mobile applications for student support
• SMS or WhatsApp-based query systems
• Internal student support systems

License

This model is provided for educational purposes. Please contact Abhinav Academy for commercial use.

Contact

For questions or feedback about this model, please reach out to [CONTACT_EMAIL].