language, library_name, pipeline_tag, license

language	library_name	pipeline_tag	license
en	transformers	text-generation	mit

KΛPPY

KΛPPY is a lightweight conversational language model built on the TinyLlama architecture and fine-tuned using the Alpaca instruction dataset.

The model is designed for lightweight chatbot experimentation, local inference, and educational purposes.

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Project Repository

The full KΛPPY chatbot project, inference pipeline, and application source code are available on GitHub:

https://github.com/AM8-3568/Kappy

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Features

• TinyLlama-based conversational model
• Fine-tuned on Alpaca instruction data
• Lightweight and efficient
• Compatible with Hugging Face Transformers
• Supports both CPU and GPU inference
• Suitable for local offline chatbot usage

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Usage

from transformers import (
    AutoTokenizer,
    AutoModelForCausalLM
)

model_name = "AM8-3568/Kappy-model"

tokenizer = AutoTokenizer.from_pretrained(
    model_name
)

model = AutoModelForCausalLM.from_pretrained(
    model_name
)

prompt = "What is artificial intelligence?"

inputs = tokenizer(
    prompt,
    return_tensors="pt"
)

outputs = model.generate(
    **inputs,
    max_new_tokens=100
)

response = tokenizer.decode(
    outputs[0],
    skip_special_tokens=True
)

print(response)

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Model Files

This repository contains:

• model.safetensors
• config.json
• generation_config.json
• tokenizer.json
• tokenizer_config.json
• chat_template.jinja

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Limitations

As a compact language model, KΛPPY may occasionally:

• Struggle with complex reasoning tasks
• Generate repetitive responses
• Produce hallucinated or inaccurate information
• Lose consistency during long conversations
• Perform below larger language models on advanced tasks

These limitations are expected for smaller language models and can be improved through additional fine-tuning, larger datasets, and more advanced architectures.

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Intended Use

KΛPPY is intended for:

• Educational projects
• Local chatbot experimentation
• Lightweight conversational AI research
• Learning Transformer inference pipelines

This model is not intended for production-critical or high-risk applications.

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Base Model

• TinyLlama

Dataset

• Alpaca Instruction Dataset