Update README.md

README.md

@@ -1,6 +1,6 @@
 ---
 library_name: diffusers
-base_model: segmind/SSD-1B
+base_model: segmind/Segmind-Vega
 tags:
 - lora
 - text-to-image
@@ -8,18 +8,18 @@ license: openrail++
 inference: false
 ---
 
-# Latent Consistency Model (LCM) LoRA: SSD-Tiny
+# Latent Consistency Model (LCM) LoRA: Segmind-Vega
 
 Latent Consistency Model (LCM) LoRA was proposed in [LCM-LoRA: A universal Stable-Diffusion Acceleration Module](https://arxiv.org/abs/2311.05556) 
 by *Simian Luo, Yiqin Tan, Suraj Patil, Daniel Gu et al.*
 
-It is a distilled consistency adapter for [`segmind/SSD-Tiny`]("https://huggingface.co/segmind/SSD-1B") that allows
+It is a distilled consistency adapter for [`segmind/Segmind-Vega`]("https://huggingface.co/segmind/Segmind_Vega") that allows
 to reduce the number of inference steps to only between **2 - 8 steps**.
 
 | Model                                                                      | Params / M | 
 |----------------------------------------------------------------------------|------------|
 | [lcm-lora-sdv1-5](https://huggingface.co/latent-consistency/lcm-lora-sdv1-5)   | 67.5       |
-| [**lcm-lora-ssd-tiny**](https://huggingface.co/segmind/lcm-lora-ssd-tiny)   | **62.7**        |
+| [**Segmind-VegaRT**](https://huggingface.co/segmind/Segmind-VegaRT)   | **62.7**        |
 | [lcm-lora-sdxl](https://huggingface.co/latent-consistency/lcm-lora-sdxl) | 197  |
 
 ## Usage
@@ -35,15 +35,15 @@ pip install --upgrade diffusers transformers accelerate peft
 
 ### Text-to-Image
 
-Let's load the base model `segmind/SSD-Tiny` first. Next, the scheduler needs to be changed to [`LCMScheduler`](https://huggingface.co/docs/diffusers/v0.22.3/en/api/schedulers/lcm#diffusers.LCMScheduler) and we can reduce the number of inference steps to just 2 to 8 steps.
+Let's load the base model `segmind/Segmind-Vega` first. Next, the scheduler needs to be changed to [`LCMScheduler`](https://huggingface.co/docs/diffusers/v0.22.3/en/api/schedulers/lcm#diffusers.LCMScheduler) and we can reduce the number of inference steps to just 2 to 8 steps.
 Please make sure to either disable `guidance_scale` or use values between 1.0 and 2.0.
 
 ```python
 import torch
 from diffusers import LCMScheduler, AutoPipelineForText2Image
 
-model_id = "segmind/SSD-Tiny"
-adapter_id = "segmind/lcm-lora-ssd-tiny"
+model_id = "segmind/Segmind-Vega"
+adapter_id = "segmind/Segmind-VegaRT"
 
 pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16")
 pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
@@ -60,4 +60,4 @@ prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
 image = pipe(prompt=prompt, num_inference_steps=4, guidance_scale=0).images[0]
 ```
 
-![SSD-Tiny LCM LoRA Image]()
+![Segmind-VegaRT Image]()