Update README.md

README.md

@@ -151,9 +151,9 @@ Update your own personal inference settings to generate different styles of imag
 - settings:
 
   model:
-    ckpt: "/path/to/ckpt"           # if ckpt is "", you should use `--ckpt` for passing model path when using `lumina` cli.
-    ckpt_lm: ""                     # if ckpt is "", you should use `--ckpt_lm` for passing model path when using `lumina` cli.
-    token: ""                       # if LLM is a huggingface gated repo, you should input your access token from huggingface and when token is "", you should `--token` for accessing the model.
+    ckpt: ""
+    ckpt_lm: ""
+    token: ""
 
   transport:
     path_type: "Linear"             # option: ["Linear", "GVP", "VP"]
@@ -169,41 +169,17 @@ Update your own personal inference settings to generate different styles of imag
     likelihood: false               # option: true or false
 
   infer:
-      resolution: "1024x1024"     # option: ["1024x1024", "512x2048", "2048x512", "(Extrapolation) 1664x1664", "(Extrapolation) 1024x2048", "(Extrapolation) 2048x1024"]
-      num_sampling_steps: 60      # range: 1-1000
-      cfg_scale: 4.               # range: 1-20
-      solver: "euler"             # option: ["euler", "dopri5", "dopri8"]
-      t_shift: 4                  # range: 1-20 (int only)
-      ntk_scaling: true           # option: true or false
-      proportional_attn: true     # option: true or false
-      seed: 0                     # rnage: any number
+      resolution: "1024x1024"       # option: ["1024x1024", "512x2048", "2048x512", "(Extrapolation) 1664x1664", "(Extrapolation) 1024x2048", "(Extrapolation) 2048x1024"]
+      num_sampling_steps: 60        # range: 1-1000
+      cfg_scale: 4.                 # range: 1-20
+      solver: "euler"               # option: ["euler", "dopri5", "dopri8"]
+      t_shift: 4                    # range: 1-20 (int only)
+      scaling_method: "Time-aware"  # option: ["Time-aware", "None"]
+      scale_watershed: 0.3          # range: 0.0-1.0
+      proportional_attn: true       # option: true or false
+      seed: 0                       # rnage: any number
 ```
 
-- model:
-  - `ckpt`: lumina-next-t2i checkpoint path from [huggingface repo](https://huggingface.co/Alpha-VLLM/Lumina-Next-T2I) containing `consolidated*.pth` and `model_args.pth`.
-  - `ckpt_lm`: LLM checkpoint.
-  - `token`: huggingface access token for accessing gated repo.
-- transport: 
-  - `path_type`: the type of path for transport: 'Linear', 'GVP' (Geodesic Vector Pursuit), or 'VP' (Vector Pursuit).
-  - `prediction`: the prediction model for the transport dynamics.
-  - `loss_weight`: the weighting of different components in the loss function, can be 'velocity' for dynamic modeling, 'likelihood' for statistical consistency, or None for no weighting
-  - `sample_eps`: sampling in the transport model.
-  - `train_eps`: training to stabilize the learning process.
-- ode:
-  - `atol`: Absolute tolerance for the ODE solver. (options: ["Linear", "GVP", "VP"])
-  - `rtol`: Relative tolerance for the ODE solver. (option: ["velocity", "score", "noise"])
-  - `reverse`: run the ODE solver in reverse. (option: [None, "velocity", "likelihood"])
-  - `likelihood`: Enable calculation of likelihood during the ODE solving process.
-- infer
-  - `resolution`: generated image resolution.
-  - `num_sampling_steps`: sampling step for generating image.
-  - `cfg_scale`: classifier-free guide scaling factor
-  - `solver`: solver for image generation.
-  - `t_shift`: time shift factor.
-  - `ntk_scaling`: ntk rope scaling factor.
-  - `proportional_attn`: Whether to use proportional attention.
-  - `seed`: random initialization seeds.
-
 1. Run with CLI
 
 inference command: