Model Details
Full Model IDnanonets/Nanonets-OCR2-3B
Pipeline / Taskimage-text-to-text
Librarytransformers
Downloads (all-time)662.2K
Likes500
Last Modified10/16/2025
Author / Orgnanonets
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-text-to-text", model="nanonets/Nanonets-OCR2-3B")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsqwen2_5_vlimage-text-to-textOCRimage-to-textpdf2markdownVQAconversationalmultilingualbase_model:Qwen/Qwen2.5-VL-3B-Instructbase_model:finetune:Qwen/Qwen2.5-VL-3B-Instructeval-resultstext-generation-inferenceendpoints_compatibleregion:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: image-text-to-text
This model is designed for the image-text-to-text task. Explore more models for this use case.
All image-text-to-text Models →📊 Popularity
⬇ Downloads662.2K
❤️ Community Likes500
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.