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nanoVLM-encoder-free
ndrugov/nanoVLM-encoder-free
nanoVLM-encoder-free is a image-text-to-text model from ndrugov. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for nanovlm. The card lists the license as mit.
Encoder-free nanoVLM is a minimal Vision-Language Model with no vision encoder. Images are resized (aspect-ratio preserving), patchified, and fed as raw pixel patches straight into the language model via a thin embedd…
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.safetensors3.5 GB · 100%
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Model card
From the Hugging Face model README
Encoder-free nanoVLM is a minimal Vision-Language Model with no vision encoder. Images are resized (aspect-ratio preserving), patchified, and fed as raw pixel patches straight into the language model via a thin embedder + projector — the number of image ("soft") tokens varies with image size. The language backbone is a HuggingFace causal LM (Qwen/Qwen3-1.7B by default).
Usage:
This is a custom architecture, so the model is loaded with the repo's own code (not transformers directly).
Clone the repo, install its dependencies, then:
from models.vision_language_model import VisionLanguageModel
model = VisionLanguageModel.from_pretrained("ndrugov/nanoVLM-encoder-free")
- Task
- Image-Text-to-Text
- Library
- nanovlm
- License
- mit
- Created
- Jun 22, 2026
- Updated
- Jun 23, 2026