Update README.md

README.md

@@ -73,8 +73,8 @@ pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], te
 pipeline.load_textual_inversion(state_dict["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
         
 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"
+prompt = f"a {instance_token}masterpiece, best quality, 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 = "nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, bad feet"
 image = pipeline(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")
 ```