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@@ -30,7 +30,7 @@ This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://hugg
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  We have two ways of using our model for this application. The first is the recommended `t2v_metrics` approach which we recommend. The latter is a back-up approach directly using Qwen2.5-VL's inference demo.
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- 1. `t2v_metrics` Approach
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  ```python
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  # Install the package using: pip install git+https://github.com/chancharikmitra/t2v_metrics.git
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@@ -120,7 +120,7 @@ print(f"Score: {score:.4f}")
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  We have two ways of using our model for this application. The first is the recommended `t2v_metrics` approach which we recommend. The latter is a back-up approach directly using Qwen2.5-VL's inference demo.
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- 1. `t2v_metrics` Approach
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  ```python
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  # Install the package using: pip install git+https://github.com/chancharikmitra/t2v_metrics.git
 
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  We have two ways of using our model for this application. The first is the recommended `t2v_metrics` approach which we recommend. The latter is a back-up approach directly using Qwen2.5-VL's inference demo.
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+ 1. `t2v_metrics` Approach (recommended)
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  ```python
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  # Install the package using: pip install git+https://github.com/chancharikmitra/t2v_metrics.git
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  We have two ways of using our model for this application. The first is the recommended `t2v_metrics` approach which we recommend. The latter is a back-up approach directly using Qwen2.5-VL's inference demo.
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+ 1. `t2v_metrics` Approach (recommended)
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  ```python
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  # Install the package using: pip install git+https://github.com/chancharikmitra/t2v_metrics.git