Refined v11
Rebuilt from the ground up.
How to use configuration file (.yaml) :
Simply drag and drop the .yaml into the same location of the model. Make sure the name matches the name of the model.
Note : To use the config file with the fp16 version of the model. The config must be renamed to match the name of the model.
So, Refined_v11-fp16.safetensors config would be Refined_v11-fp16.yaml
Refined_v11-fp16.safetensors
Refined_v11-fp16.yaml
What's included :
Refined_v11.safetensors | Full model | FP32 | Safetensors
Refined_v11.yaml | Config
Refined_v11-fp16 | Pruned model | FP16 | Safetensors
Refined_v11.ckpt | Full model | FP16 | PyTorch (.ckpt)
Refined v11
Rebuilt from the ground up.
How to use configuration file (.yaml) :
Simply drag and drop the .yaml into the same location of the model. Make sure the name matches the name of the model.
Note : To use the config file with the fp16 version of the model. The config must be renamed to match the name of the model.
So,
Refined_v11-fp16.safetensors
config would beRefined_v11-fp16.yaml
What's included :
Refined_v11.safetensors | Full model | FP32 | Safetensors
Refined_v11.yaml | Config
Refined_v11-fp16 | Pruned model | FP16 | Safetensors
Refined_v11.ckpt | Full model | FP16 | PyTorch (.ckpt)