Update README.md

README.md

@@ -23,6 +23,59 @@ license: creativeml-openrail-m
 
 <Gallery />
 
+**The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.**
+
+## Model description 
+
+**prithivMLmods/Canopus-Car-Flux-Dev-LoRA**
+
+Image Processing Parameters 
+
+| Parameter                 | Value  | Parameter                 | Value  |
+|---------------------------|--------|---------------------------|--------|
+| LR Scheduler              | constant | Noise Offset              | 0.03   |
+| Optimizer                 | AdamW8bit | Multires Noise Discount   | 0.1    |
+| Network Dim               | 64     | Multires Noise Iterations | 10     |
+| Network Alpha             | 32     | Repeat & Steps           | 22 & 1.5K+ |
+| Epoch                     | 15     | Save Every N Epochs       | 1      |
+
+Labeling: florence2-en(natural language & English) 
+
+Total Images Used for Training : 40+ [ Hi-RES ]
+
+& More ...............
+
+## Trigger prompts
+
+    A black ford mustang parked in the parking lot, in the style of futurism influence, uhd image, furaffinity, focus, street photography, thin steel forms, 32k uhd --ar 2:3 --v 5
+    
+    Ferrari car f3 458 tt, in the style of liam wong, fujifilm x-t4, multiple exposure, tsubasa nakai, uhd image, pinturicchio, crimson --ar 16:9 --v 5.2
+    
+    Bugatti Veyron in cobalt blue metallic, high detail, octane render, 8k
+
+ 
+| Parameter       | Value                                                                                 |
+|-----------------|---------------------------------------------------------------------------------------|
+| Prompt          | Bugatti Veyron in cobalt blue metallic, high detail, octane render, 8k |
+| Sampler         | euler                                                                                 |
+
+## Setting Up
+
+```
+import torch
+from pipelines import DiffusionPipeline
+
+base_model = "black-forest-labs/FLUX.1-dev"
+pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
+
+lora_repo = "prithivMLmods/Canopus-Car-Flux-Dev-LoRA"
+trigger_word = "car"  # Leave trigger_word blank if not used.
+pipe.load_lora_weights(lora_repo)
+
+device = torch.device("cuda")
+pipe.to(device)
+```
+
 
 ## Trigger words