Update README.md

README.md

@@ -12,9 +12,9 @@ pipeline_tag: video-to-video
 library_name: diffusers
 ---
 
-# LTX Video Spatial Upscaler 0.9.7 Model Card
+# LTX Video Spatial Upscaler 0.9.8 Model Card
 
-This model card focuses on the LTX Video Spatial Upscaler 0.9.7, a component model designed to work in conjunction with the LTX-Video generation models. 
+This model card focuses on the LTX Video Spatial Upscaler 0.9.8, a component model designed to work in conjunction with the LTX-Video generation models. 
 The main LTX-Video codebase is available [here](https://github.com/Lightricks/LTX-Video).
 
 LTX-Video is the first DiT-based video generation model capable of generating high-quality videos in real-time. It produces 30 FPS videos at a 1216×704 resolution faster than they can be watched. Trained on a large-scale dataset of diverse videos, the model generates high-resolution videos with realistic and varied content.
@@ -34,8 +34,8 @@ We provide a model for both text-to-video as well as image+text-to-video usecase
 
 
 **This upscaler model is compatible with and can be used to improve the output quality of videos generated by both:**
-*   `Lightricks/LTX-Video-0.9.7-dev`
-*   `Lightricks/LTX-Video-0.9.7-distilled`
+*   `Lightricks/LTX-Video-0.9.8-dev`
+*   `Lightricks/LTX-Video-0.9.8-distilled`
 
 
 ## Model Details
@@ -43,7 +43,7 @@ We provide a model for both text-to-video as well as image+text-to-video usecase
 - **Model type:** Latent Diffusion Video Spatial Upscaler
 - **Input:** Latent video frames from an LTX Video model.
 - **Output:** Higher-resolution latent video frames.
-- **Compatibility:** can be used with `Lightricks/LTX-Video-0.9.7-dev` and `Lightricks/LTX-Video-0.9.7-distilled`.
+- **Compatibility:** can be used with `Lightricks/LTX-Video-0.9.7-dev` and `Lightricks/LTX-Video-0.9.8-distilled`.
 
 ## Usage
 
@@ -120,7 +120,7 @@ from diffusers.utils import export_to_video, load_image
 
 # Choose your base LTX Video model:
 # base_model_id = "Lightricks/LTX-Video-0.9.7-dev"
-base_model_id = "Lightricks/LTX-Video-0.9.7-distilled" # Using distilled for this example
+base_model_id = "Lightricks/LTX-Video-0.9.8-distilled" # Using distilled for this example
 
 # 0. Load base model and upsampler
 pipe = LTXConditionPipeline.from_pretrained(base_model_id, torch_dtype=torch.bfloat16)