awal-gpt-v0.2-7b/README.md

language, license, library_name, pipeline_tag, tags

language	license	library_name	pipeline_tag	tags
ber tmz ar en	apache-2.0	transformers	text-generation	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

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:

@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.