Update README.md

README.md

@@ -70,7 +70,11 @@ state_dict = load_file(embedding_path)
 pipeline.load_textual_inversion(state_dict["clip_l"], token=[], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
 pipeline.load_textual_inversion(state_dict["clip_g"], token=[], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
         
-image = pipeline('In the style of Terada,colorful, anime-style, illustration, girl, yellow jacket, blonde hair, two buns, peace sign, hands, rainbow gradient, brightness, cheerfulness, small confetti, festive atmosphere, central position, joy, positivity.').images[0]
+instance_token = "<s0><s1>"
+prompt = f"a {instance_token}full-length phoor portrait，Vibrant, solo, 1girl, smile, long hair, hair between eyes, multicolored eyes, hooded jacket, open jacket, shirt, long sleeves, ribbon, best quality, perfect anatomy, highres, absurdres{instance_token}  "
+negative_prompt = "bad_prompt_version2, (worst quality, low quality:1.4), realistic, lip, nose, tooth, rouge, lipstick, eyeshadow, abs, muscular, rib, (depth of field, bokeh, blurry:1.4), greyscale"
+image = pipe(prompt=prompt, negative_prompt = negative_prompt, num_inference_steps=100, cross_attention_kwargs={"scale": 1.0},width = 960, height=1280).images[0]
+image.save("./save.png")
 ```
 
 For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)