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Hi there,
If I want to train a new ESRGAN model, a 2.5x upsampling/downsampling factor, for example, how do I get the corresponding pre-trained PSNR model?
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(In both local and cloud storage settings)
Also, for better distribution you might want to integrate with vLLM, similarly to how tensorizer is supported there
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I am trying to look at a scenario where the global temperature changes in future and it affects the total solar potential of a region. The change in solar potential is based on various calculation don…
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Hello!
Thank you for development of MOFA.
In my work, I wanted to use MOFA latent factors to predict a phenotype.
To prevent data leakage between my train and test set, I wanted to train the M…
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## Summary
When a model is transformed using the model scaling transformation, `Expressions` are created on the scaled model, but variable scaling factors are not added to them like they are for `C…
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模型类型为PP-YOLOE_plus-L
Inference.yml文件内容如下：
```
mode: paddle
draw_threshold: 0.5
metric: COCO
use_dynamic_shape: false
Global:
pipeline_name: PP-YOLOE_plus-L
model_name: PP-YOLOE_plus-L
ar…
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I am using `develop` branch and I have encountered this issue when I want to extend [this example](https://github.com/borglab/gtsam/blob/develop/gtsam_unstable/examples/FixedLagSmootherExample.cpp) w…
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this is currently handled by list in `garak/cli.py` and `garak/generators/__init__.py`
would be better to have just one list in one place
might be best to have this specified in the generator cl…
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For example, we want to do a type III ANOVA, so we fit a linear model with categorical predictors and use the car::Anova function:
```r
some_linear_model
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### Describe the issue
Inference results are outputting abnormally when using YOLOv7 models with TensorRT EP.
We have confirmed that the results are normal when using CPU and CUDA.
The issue wa…