Implementation:Open compass VLMEvalKit IDEFICS
| Field | Value |
|---|---|
| source | VLMEvalKit |
| domain | Vision, Model_Architecture |
Overview
VLM adapter for the IDEFICS model enabling benchmark evaluation in VLMEvalKit.
Description
IDEFICS inherits from BaseModel and wraps the IDEFICS model for use within the VLMEvalKit evaluation framework. It initializes the model and tokenizer/processor from a HuggingFace model path (default: HuggingFaceM4/idefics-9b-instruct) and provides the generate_inner method for inference. Also includes IDEFICS2 adapter class for the IDEFICS2 model family.
Usage
Register in vlmeval/config.py via supported_VLM and invoke through the standard evaluation pipeline.
Code Reference
- Source:
vlmeval/vlm/idefics.py, Lines: L1-309 - Import:
from vlmeval.vlm.idefics import IDEFICS
Signature:
class IDEFICS(BaseModel):
INSTALL_REQ = False
INTERLEAVE = True
def __init__(self, model_path='HuggingFaceM4/idefics-9b-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.idefics import IDEFICS
model = IDEFICS(model_path='path/to/model')
response = model.generate_inner(message)