|
|
| import gradio as gr |
| import torch |
| import requests |
| from PIL import Image |
| from io import BytesIO |
| from transformers import AutoProcessor, AutoModelForImageTextToText, BitsAndBytesConfig |
|
|
| model_id = 'Arabic250/gemma-4-E4B-it' |
| quantization_config = BitsAndBytesConfig( |
| load_in_4bit=True, |
| bnb_4bit_compute_dtype=torch.bfloat16, |
| bnb_4bit_quant_type='nf4', |
| bnb_4bit_use_double_quant=True |
| ) |
|
|
| processor = AutoProcessor.from_pretrained(model_id) |
| model = AutoModelForImageTextToText.from_pretrained( |
| model_id, |
| quantization_config=quantization_config, |
| device_map='auto' |
| ) |
|
|
| def predict_chat(message, history): |
| try: |
| parts = message.split(' ', 1) |
| has_url = parts[0].startswith('http') |
| if has_url: |
| image_url = parts[0] |
| user_prompt = parts[1] if len(parts) > 1 else 'صف هذه الصورة' |
| response = requests.get(image_url, stream=True) |
| image = Image.open(BytesIO(response.content)).convert('RGB') |
| else: |
| image = Image.new('RGB', (224, 224), color = (255, 255, 255)) |
| user_prompt = message |
|
|
| messages = [{'role': 'user', 'content': [{'type': 'image'}, {'type': 'text', 'text': user_prompt}]}] |
| prompt = processor.apply_chat_template(messages, add_generation_prompt=True) |
| inputs = processor(text=prompt, images=image, return_tensors='pt').to(model.device) |
| |
| with torch.inference_mode(): |
| output = model.generate(**inputs, max_new_tokens=512, do_sample=True, temperature=0.7) |
| |
| return processor.decode(output[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True).strip() |
| except Exception as e: return f'Error: {str(e)}' |
|
|
| chat_interface = gr.ChatInterface(fn=predict_chat, title='Gemma-4-E4B-it Arabic Space') |
| chat_interface.launch() |
|
|
