finetuned from Qwen
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation import GenerationConfig
tokenizer = AutoTokenizer.from_pretrained("huskyhong/noname-ai-v2_3-light", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("huskyhong/noname-ai-v2_3-light", device_map="auto", trust_remote_code=True).eval() # 采用gpu加载模型
# model = AutoModelForCausalLM.from_pretrained("huskyhong/noname-ai-v2_3-light", device_map="cpu", trust_remote_code=True).float() # 采用cpu加载模型
model.generation_config = GenerationConfig.from_pretrained("huskyhong/noname-ai-v2_3-light", trust_remote_code=True) # 可指定不同的生成长度、top_p等相关超参
prompt = "请帮我编写一个技能，技能效果如下：" + input("请输入技能效果：")
response, history = model.chat(tokenizer, prompt, history = [])
print(response)
prompt = "请帮我编写一张卡牌，卡牌效果如下：" + input("请输入卡牌效果：")
response, history = model.chat(tokenizer, prompt, history = [])
print(response)
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