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*This model was released on 2025-10-01 and added to Hugging Face Transformers on 2026-02-23.*

# ModernVBert

<div class="flex flex-wrap space-x-1">
<img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-DE3412?style=flat&logo=pytorch&logoColor=white">
<img alt="FlashAttention" src="https://img.shields.io/badge/%E2%9A%A1%EF%B8%8E%20FlashAttention-eae0c8?style=flat">
<img alt="SDPA" src="https://img.shields.io/badge/SDPA-DE3412?style=flat&logo=pytorch&logoColor=white">
</div>

## Overview

ModernVBert is a Vision-Language encoder that combines [ModernBert](modernbert) with a [SigLIP](siglip) vision encoder. It is optimized for visual document understanding and retrieval tasks.

The model was introduced in [ModernVBERT: Towards Smaller Visual Document Retrievers](https://huggingface.co/papers/2510.01149).

<hfoptions id="usage">
<hfoption id="Python">

```python
import torch
from PIL import Image
from huggingface_hub import hf_hub_download
from transformers import AutoModelForMaskedLM, AutoProcessor

processor = AutoProcessor.from_pretrained("./mvb")
model = AutoModelForMaskedLM.from_pretrained("./mvb")

image = Image.open(hf_hub_download("HuggingFaceTB/SmolVLM", "example_images/rococo.jpg", repo_type="space"))
text = "This [MASK] is on the wall."

# Create input messages
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image"},
            {"type": "text", "text": text}
        ]
    },
]

# Prepare inputs
prompt = processor.apply_chat_template(messages)
inputs = processor(text=prompt, images=[image], return_tensors="pt")

# Inference
with torch.no_grad():
  outputs = model(**inputs)

# To get predictions for the mask:
masked_index = inputs["input_ids"][0].tolist().index(processor.tokenizer.mask_token_id)
predicted_token_id = outputs.logits[0, masked_index].argmax(axis=-1)
predicted_token = processor.tokenizer.decode(predicted_token_id)
print("Predicted token:", predicted_token)  # Predicted token: painting
```

</hfoption>
</hfoptions>

## ModernVBertConfig

[[autodoc]] ModernVBertConfig

## ModernVBertModel

[[autodoc]] ModernVBertModel
    - forward

## ModernVBertForMaskedLM

[[autodoc]] ModernVBertForMaskedLM
    - forward

## ModernVBertForSequenceClassification

[[autodoc]] ModernVBertForSequenceClassification
    - forward

## ModernVBertForTokenClassification

[[autodoc]] ModernVBertForTokenClassification
    - forward