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base_model: Qwen/Qwen2.5-7B-Instruct
library_name: transformers
model_name: sanity-arabic-chatbot
tags:
  - arabic
  - egyptian-arabic
  - dialectal-arabic
  - colloquial
  - chat
  - chatbot
  - lora
  - peft
  - qwen2.5
licence: license
datasets:
  - kokojake/oasst2_egyptian_arabic_convs
  - kokojake/lmsys_egyptian_arabic_convs
  - Omar-youssef/islamic-qa-egyptian-arabic
  - miscovery/General_Facts_in_English_Arabic_Egyptian_Arabic
  - Elfsong/Qwen3_4B_Arabic_200-responses-Egyptian
language:
  - ar

Model Card for sanity-arabic-chatbot

This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct. It has been trained using TRL.

Quick start

from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="MenemAI/sanity-arabic-chatbot", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

This model was trained with SFT.

Framework versions

TRL: 1.3.0
Transformers: 5.8.0
Pytorch: 2.11.0
Datasets: 4.8.5
Tokenizers: 0.22.2

Citations

Cite TRL as:

@software{vonwerra2020trl,
  title   = {{TRL: Transformers Reinforcement Learning}},
  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
  license = {Apache-2.0},
  url     = {https://github.com/huggingface/trl},
  year    = {2020}
}