---
language:
- en

library_name: transformers

pipeline_tag: text-generation

license: 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.

---

# Project Repository

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

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

---

# 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

---

# Usage

```python
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)
```

---

# Model Files

This repository contains:

- `model.safetensors`
- `config.json`
- `generation_config.json`
- `tokenizer.json`
- `tokenizer_config.json`
- `chat_template.jinja`

---

# 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.

---

# 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.

---

# Base Model

- TinyLlama

# Dataset

- Alpaca Instruction Dataset