Update README.md

README.md

@@ -38,14 +38,14 @@ MODEL_NAME = "p1atdev/dart-v1-sft"
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, trust_remote_code=True) # trust_remote_code is required for tokenizer
 model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.bfloat16)
 
-prompt = "<|bos|><rating>rating:sfw, rating:general</rating><copyright>original</copyright><character></character><general>1girl, "
+prompt = "<|bos|><rating>rating:sfw, rating:general</rating><copyright>original</copyright><character></character><general><|long|>1girl<|input_end|>"
 inputs = tokenizer(prompt, return_tensors="pt").input_ids
 
 with torch.no_grad():
   outputs = model.generate(inputs, generation_config=generation_config)
 
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
-# rating:sfw, rating:general, original, 1girl, ahoge, black hair, blue eyes, blush, closed mouth, ear piercing, earrings, jewelry, looking at viewer, mole, mole under eye, piercing, portrait, shirt, short hair, solo, white shirt
+# rating:sfw, rating:general, 1girl, ahoge, braid, closed eyes, collared dress, dress, flower, full body, hair flower, hair ornament, long hair, night, night sky, outdoors, parted lips, pink flower, pink hair, short sleeves, sky, solo, straight hair, sunflower, very long hair, white flower
 ```
 
 #### Flash attention (optional)
@@ -86,7 +86,7 @@ ort_model = ORTModelForCausalLM.from_pretrained(MODEL_NAME)
 # qunatized version
 # ort_model = ORTModelForCausalLM.from_pretrained(MODEL_NAME, file_name="model_quantized.onnx")
 
-prompt = "<|bos|><rating>rating:sfw, rating:general</rating><copyright>original</copyright><character></character><general>1girl, "
+prompt = "<|bos|><rating>rating:sfw, rating:general</rating><copyright>original</copyright><character></character><general><|long|>1girl<|input_end|>"
 inputs = tokenizer(prompt, return_tensors="pt").input_ids
 
 with torch.no_grad():