Implementation:Open compass VLMEvalKit MiniMonkey
Appearance
| Field | Value |
|---|---|
| source | VLMEvalKit |
| domain | Vision, Model_Architecture |
Overview
VLM adapter for the MiniMonkey model enabling benchmark evaluation in VLMEvalKit.
Description
MiniMonkey inherits from BaseModel and wraps the MiniMonkey model for use within the VLMEvalKit evaluation framework. It initializes the model and tokenizer/processor from a HuggingFace model path (default: mx262/MiniMokney) 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/minimonkey.py, Lines: L1-492 - Import:
from vlmeval.vlm.minimonkey import MiniMonkey
Signature:
class MiniMonkey(BaseModel):
INSTALL_REQ = False
INTERLEAVE = True
def __init__(self, model_path='mx262/MiniMokney', **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.minimonkey import MiniMonkey
model = MiniMonkey(model_path='path/to/model')
response = model.generate_inner(message)
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Principle
Implementation
Heuristic
Environment