Update README.md

README.md

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 # SEEDRA
 
-![img](./assets/seedra.png)
+![img](./seedra.png)
 
 ## MODEL DOWNLOAD
 
@@ -43,13 +43,13 @@ By contrast, smaller “core” models (1 B, 3 B, 8 B, 14 B) often struggle
 
 ## How to use SEEDRA
 
-![img](./assets/tta.png)
+![img](./tta.png)
 
 1. If you need to build a special instruction dataset or have a domain-specific training dataset, you can augment it using SEEDRA.
 2. For example, Qwen 2.5 is a very powerful model, strong in Chinese and English but somewhat weak in Korean. In such cases, you can use SEEDRA to augment Korean data—using varied expressions and sentence orders to secure more subtoken coverage and strengthen its Korean capabilities.
 3. In a multimodal workflow, you can convert SEEDRA‑generated text into speech using a tool like OuteTTS, then feed that synthesized audio into an ASR (automatic speech recognition) model as additional training or validation data.
 
-![img](./assets/mma.png)
+![img](./mma.png)
 
 ## DEMO