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Implementation:Open compass VLMEvalKit Mantis

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Revision as of 13:30, 16 February 2026 by Admin (talk | contribs) (Auto-imported from implementations/Open_compass_VLMEvalKit_Mantis.md)
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Field Value
source VLMEvalKit
domain Vision, Model_Architecture

Overview

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

Description

Mantis inherits from BaseModel and wraps the Mantis model for use within the VLMEvalKit evaluation framework. It initializes the model and tokenizer/processor from a HuggingFace model path (default: TIGER-Lab/Mantis-8B-siglip-llama3) and provides the generate_inner method for inference. Supports multiple model architectures including LLaVA, Fuyu, and IDEFICS2 backends.

Usage

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

Code Reference

  • Source: vlmeval/vlm/mantis.py, Lines: L1-201
  • Import: from vlmeval.vlm.mantis import Mantis

Signature:

class Mantis(BaseModel):
    INSTALL_REQ = True
    INTERLEAVE = True
    def __init__(self, model_path='TIGER-Lab/Mantis-8B-siglip-llama3', **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.mantis import Mantis
model = Mantis(model_path='path/to/model')
response = model.generate_inner(message)

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