Implementation:Open compass VLMEvalKit TransCoreM
| Field | Value |
|---|---|
| source | VLMEvalKit |
| domain | Vision, Model_Architecture |
Overview
VLM adapter for the TransCore-M model enabling benchmark evaluation in VLMEvalKit.
Description
TransCoreM inherits from BaseModel and wraps the TransCore-M model for use within the VLMEvalKit evaluation framework. It initializes the model and tokenizer/processor from a HuggingFace model path (default: model_path (required)) and provides the generate_inner method for inference. Uses TransCoreMQWenForCausalLM with custom Qwen-based architecture and vision tower loading.
Usage
Register in vlmeval/config.py via supported_VLM and invoke through the standard evaluation pipeline.
Code Reference
- Source:
vlmeval/vlm/transcore_m.py, Lines: L1-162 - Import:
from vlmeval.vlm.transcore_m import TransCoreM
Signature:
class TransCoreM(BaseModel):
INSTALL_REQ = True
INTERLEAVE = False
def __init__(self, model_path='model_path (required)', **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.transcore_m import TransCoreM
model = TransCoreM(model_path='path/to/model')
response = model.generate_inner(message)