Update README.md

README.md

@@ -10,8 +10,49 @@ library_name: diffusers
 
 ## How to use the model
 
-_TBD_
+### Install needed libraries
+
+```
+pip install git+https://github.com/huggingface/diffusers.git transformers==4.42.4 accelerate xformers peft sentencepiece protobuf -q
+```
+
+### Execution code
+
+```python
+import numpy as np
+import random
+import torch
+from diffusers import  DiffusionPipeline, FlowMatchEulerDiscreteScheduler, AutoencoderTiny, AutoencoderKL
+from transformers import CLIPTextModel, CLIPTokenizer,T5EncoderModel, T5TokenizerFast
+
+dtype = torch.bfloat16
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype).to(device)
+pipe = DiffusionPipeline.from_pretrained("mann-e/mann-e_flux", torch_dtype=dtype, vae=taef1).to(device)
+torch.cuda.empty_cache()
+
+MAX_SEED = np.iinfo(np.int32).max
+MAX_IMAGE_SIZE = 2048
+
+seed = random.randint(0, MAX_SEED)
+generator = torch.Generator().manual_seed(seed)
+
+prompt = "an astronaut riding a horse"
+
+pipe(
+            prompt=f"{prompt}",
+            guidance_scale=3.5,
+            num_inference_steps=10,
+            width=720,
+            height=1280,
+            generator=generator,
+            output_type="pil"
+        ).images[0].save("output.png")
+```
 
 ## Tips and Tricks
 
-_TBD_
+1. Adding `mj-v6.1-style` to the prompts specially the cinematic and photo realistic prompts can make the result quality high as hell! Give it a try.
+2. The best `guidance_scale` is somewhere between 3.5 and 5.0
+3. Inference steps between 8 and 16 are working very well.