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Implementation:Open compass VLMEvalKit XGenMM

From Leeroopedia
Field Value
source VLMEvalKit
domain Vision, Model_Architecture

Overview

VLM adapter for the XGen-MM model enabling benchmark evaluation in VLMEvalKit.

Description

XGenMM inherits from BaseModel and wraps the XGen-MM model for use within the VLMEvalKit evaluation framework. It initializes the model and tokenizer/processor from a HuggingFace model path (default: Salesforce/xgen-mm-phi3-mini-instruct-interleave-r-v1.5) and provides the generate_inner method for inference.

Usage

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

Code Reference

  • Source: vlmeval/vlm/xgen_mm.py, Lines: L1-81
  • Import: from vlmeval.vlm.xgen_mm import XGenMM

Signature:

class XGenMM(BaseModel):
    INSTALL_REQ = False
    INTERLEAVE = True
    def __init__(self, model_path='Salesforce/xgen-mm-phi3-mini-instruct-interleave-r-v1.5', **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.xgen_mm import XGenMM
model = XGenMM(model_path='path/to/model')
response = model.generate_inner(message)

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