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vorenthiclabs/vorenthos-vision-coding-qwen25vl-7b
vorenthos-vision-coding-qwen25vl-7b is a image-text-to-text model from vorenthiclabs. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Fine-tuned unsloth/Qwen2-VL-7B-Instruct-bnb-4bit with Unsloth + QLoRA.
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From the Hugging Face model README
Fine-tuned unsloth/Qwen2-VL-7B-Instruct-bnb-4bit with Unsloth + QLoRA.
Qwen2.5-VL-7B is the top open-source VLM for code, OCR, and document understanding at the 7B scale. Fine-tuned here to read code screenshots, diagrams, and technical images and reproduce or explain the code they contain.
| Setting | Value |
|---|---|
| Base model | unsloth/Qwen2-VL-7B-Instruct-bnb-4bit |
| Method | QLoRA (r=16, alpha=16) |
| Precision | float16 (merged) |
| Max seq length | 2048 |
| Steps | 60 |
| Date | 2026-07-26 |
from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor
from qwen_vl_utils import process_vision_info
import torch
model_id = "vorenthiclabs/vorenthos-vision-coding-qwen25vl-7b"
processor = AutoProcessor.from_pretrained(model_id)
model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
model_id, torch_dtype=torch.float16, device_map="auto"
)
messages = [
{
"role": "user",
"content": [
{"type": "image", "image": "https://your-code-screenshot.png"},
{"type": "text", "text": "Reproduce the code shown in this screenshot."}
]
}
]
text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = processor(text=[text], images=[...], return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=1024, temperature=0.1)
print(processor.decode(output[0], skip_special_tokens=True))