Implementation:Open compass VLMEvalKit SmolVLM

Field	Value
source	VLMEvalKit
domain	Vision, Model_Architecture

Overview

VLM adapter for the SmolVLM model enabling benchmark evaluation in VLMEvalKit.

Description

SmolVLM inherits from BaseModel and wraps the SmolVLM model for use within the VLMEvalKit evaluation framework. It initializes the model and tokenizer/processor from a HuggingFace model path (default: HuggingFaceTB/SmolVLM-Instruct) and provides the generate_inner method for inference. Also includes SmolVLM2 adapter class for the SmolVLM2 model variant.

Usage

Register in vlmeval/config.py via supported_VLM and invoke through the standard evaluation pipeline.

Code Reference

Source: vlmeval/vlm/smolvlm.py, Lines: L1-869
Import: from vlmeval.vlm.smolvlm import SmolVLM

Signature:

class SmolVLM(BaseModel):
    INSTALL_REQ = True
    INTERLEAVE = True
    def __init__(self, model_path='HuggingFaceTB/SmolVLM-Instruct', **kwargs): ...
    def generate_inner(self, message, dataset=None): ...

I/O Contract

Direction	Description
Inputs	message — list of dicts with type (text/image) and value; dataset — optional dataset name for custom prompting
Outputs	generate_inner() returns str (model response text)

Usage Examples

from vlmeval.vlm.smolvlm import SmolVLM
model = SmolVLM(model_path='path/to/model')
response = model.generate_inner(message)

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Principle

Implementation

Heuristic

Environment