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AgtOwad/
nanoVLM_TQA

Name: nanoVLM_TQA
Availability: InStock

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nanoVLM is a minimal and lightweight Vision-Language Model (VLM) designed for efficient training and experimentation. Built using pure PyTorch, the entire model architecture and training logic fits within ~750 lines of code. It combines a ViT-based image encoder (SigLIP-B/16-224-85M) with a lightweight causal language model (SmolLM2-135M), resulting in a compact 222M parameter model.

For more information, check out the base model on https://huggingface.co/lusxvr/nanoVLM-222M.

Usage:

Clone the nanoVLM repository: https://github.com/huggingface/nanoVLM. Follow the install instructions and run the following code:

python

from models.vision_language_model import VisionLanguageModel

model = VisionLanguageModel.from_pretrained("AgtOwad/nanoVLM_TQA")