injazsmart/thoth_test

Qwen2.5-VL-7B-Instruct Fine-tuned with QLoRA

This model was fine-tuned using Axolotl with QLoRA on Arabic text data. It is based on Qwen/Qwen2.5-VL-7B-Instruct.

Training details

• Method: QLoRA
• Epochs: 3
• Optimizer: Paged AdamW 32bit
• Quantization: 4-bit (NF4)
• Hardware: NVIDIA H100 80GB
• Dataset: Custom Arabic instruction-style text

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("injazsmart/thoth_test")
tokenizer = AutoTokenizer.from_pretrained("injazsmart/thoth_test")

prompt = "اشرح لي معنى الذكاء الاصطناعي بلغة بسيطة"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))