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---
license: mit
metrics:
- bleu
- rouge
- meteor
- bertscore
base_model:
- liuhaotian/llava-v1.5-7b
pipeline_tag: visual-question-answering
---
# visual-qa-tem Model Card
## Model details
**base_model**
We finetune our custom data on LLava-v1.5-7b
See on :[liuhaotian/llava-v1.5-7b](https://huggingface.co/liuhaotian/llava-v1.5-7b)
**Paper or resources for more information:**
Our source code publish on : https://github.com/SmartLab-Roy/visual-qa-tem.git
### Download Model
```python
from huggingface_hub import snapshot_download
import os
# Download the model to local directory
model_path = snapshot_download(
repo_id="LabSmart/visual-qa-tem",
cache_dir="./models", # Local cache directory
resume_download=True
)
print(f"Model downloaded to: {model_path}")
```
### Quick Start
Reference [LLaVA](https://github.com/haotian-liu/LLaVA.git) for environment setup and CLI inference:
```
python -m llava.serve.cli \
--model-path "model_path from the download output"\
--image-file "path/to/your/tem_image.jpg" \
--load-4bit
``` |