Update README.md

README.md

@@ -64,11 +64,9 @@ You can use this model just as any other HuggingFace models:
 from transformers import AutoModelForCausalLM, AutoTokenizer
 model = AutoModelForCausalLM.from_pretrained('fla-hub/rwkv7-191M-world', trust_remote_code=True)
 tokenizer = AutoTokenizer.from_pretrained('fla-hub/rwkv7-191M-world', trust_remote_code=True)
-model = model.cuda()
+model = model.cuda() # Supported on Nvidia/AMD/Intel eg. model.xpu()
 prompt = "What is a large language model?"
 messages = [
-    {"role": "user", "content": "Who are you?"},
-    {"role": "assistant", "content": "I am a GPT-3 based model."},
     {"role": "user", "content": prompt}
 ]
 text = tokenizer.apply_chat_template(
@@ -81,7 +79,11 @@ model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
 
 generated_ids = model.generate(
     **model_inputs,
-    max_new_tokens=1024,
+    max_new_tokens=4096,
+    do_sample=True,
+    temperature=1.0,
+    top_p=0.3,
+    repetition_penalty=1.2
 )
 generated_ids = [
     output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)