---
language:
- ber
- tmz
- ar
- en
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- tamazight
- amazigh
- berber
- llm
- nlp
- qwen
- chatbot
- low-resource-language
- morocco
- africa
- text-generation
---

# AWAL GPT v0.2 7B

AWAL GPT v0.2 is an open-source Large Language Model fine-tuned for the Amazigh (Tamazight) language, with a primary focus on **Latin-script Tamazight used in Morocco**.

To the best of the author's knowledge, this is **the first open-source Amazigh (Tamazight Latin script) LLM developed in Morocco**.

The project aims to contribute to the preservation, digitization, and advancement of Amazigh through Artificial Intelligence and Natural Language Processing.

## Project Goals

AWAL GPT is part of a larger initiative to build a complete AI ecosystem for Tamazight, including:

- Large Language Models (LLMs)
- Intelligent Chatbots
- Speech-to-Text (ASR)
- Text-to-Speech (TTS)
- Machine Translation
- Grammar Correction
- OCR
- Retrieval-Augmented Generation (RAG)
- Voice Assistants

---

# Base Model

This model is fine-tuned from:

- Qwen2.5-7B

using instruction tuning on Amazigh datasets.

---

# Supported Language

Current focus:

- Moroccan Tamazight (Latin script)

Future versions aim to support:

- Tifinagh
- Arabic script
- Multiple Amazigh dialects (Tashelhit, Central Atlas Tamazight, Tarifit)

---

# Example

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "mohamedazelmad/awal-gpt-v0.2-7b"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

prompt = "Mani ismk?"

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

outputs = model.generate(
    **inputs,
    max_new_tokens=128
)

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

---

# Intended Uses

- Research
- Education
- Amazigh NLP
- Chatbots
- Language preservation
- AI experimentation
- Academic projects

---

# Limitations

- The model is still under active development.
- Performance may vary across different Amazigh dialects.
- Responses may contain factual inaccuracies or hallucinations.
- Not intended for high-risk applications without human verification.

---

# Roadmap (AWAL GPT V2)

The next generation will include:

- Improved reasoning
- Larger training corpus
- Better instruction following
- Speech capabilities (ASR/TTS)
- Translation system
- OCR
- RAG integration
- Voice assistant
- Public web interface
- WhatsApp integration

---

# Citation

If you use this model in your research, please cite:

```bibtex
@misc{awalgpt2026,
  title={AWAL GPT: Large Language Models for Amazigh (Tamazight)},
  author={Mohamed Azelmad},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/mohamedazelmad/awal-gpt-v0.2-7b}
}
```

---

# Contact

**Author:** Mohamed Azelmad

For collaborations, research partnerships, or contributions related to Amazigh AI and NLP, feel free to connect via LinkedIn or Hugging Face.

---

# Acknowledgements

This project builds upon open-source technologies from the AI community, including:

- Qwen
- Hugging Face Transformers
- PyTorch
- TRL
- PEFT
- Unsloth

Special thanks to everyone working on low-resource languages and open AI research.