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--- |
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library_name: transformers |
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tags: |
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- llama-factory |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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# 🤭 Please refer to https://github.com/svjack/Genshin-Impact-Character-Chat to get more info |
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# Install |
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```bash |
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pip install peft transformers bitsandbytes |
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``` |
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# Run by transformers |
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* Step 1: Generate a story Backgroud In Genshin Impact |
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```python |
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from transformers import TextStreamer, AutoTokenizer, AutoModelForCausalLM |
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from peft import PeftModel |
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tokenizer = AutoTokenizer.from_pretrained("svjack/Genshin_Impact_Qwen_1_5_Chat_sharegpt_roleplay_chat_lora_small_merged",) |
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qw_model = AutoModelForCausalLM.from_pretrained("svjack/Genshin_Impact_Qwen_1_5_Chat_sharegpt_roleplay_chat_lora_small_merged", load_in_4bit = True) |
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qw_model = qw_model.eval() |
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streamer = TextStreamer(tokenizer) |
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def qwen_hf_predict(messages, qw_model = qw_model, |
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tokenizer = tokenizer, streamer = streamer, |
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do_sample = True, |
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top_p = 0.95, |
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top_k = 40, |
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max_new_tokens = 2070, |
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max_input_length = 3500, |
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temperature = 0.9, |
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repetition_penalty = 1.0, |
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device = "cuda"): |
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encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt", |
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add_generation_prompt=True |
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) |
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model_inputs = encodeds.to(device) |
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generated_ids = qw_model.generate(model_inputs, max_new_tokens=max_new_tokens, |
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do_sample=do_sample, |
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streamer = streamer, |
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top_p = top_p, |
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top_k = top_k, |
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temperature = temperature, |
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repetition_penalty = repetition_penalty, |
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) |
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out = tokenizer.batch_decode(generated_ids)[0].split("<|im_start|>assistant")[-1].replace("<|im_end|>", "").strip() |
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return out |
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out = qwen_hf_predict([ |
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{ |
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"role": "user", |
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"content": ''' |
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人物设定: |
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下面是九条裟罗的一些基本信息 |
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性别:成年女性 |
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国籍:稻妻 |
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身份:负责治安事务的天领奉行大将 |
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性格特征:雷厉风行,以身作则 |
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这些是一段角色介绍 |
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九条裟罗有着天狗血统,却不像一般天狗那样栖居于山林间。她自幼被九条家收养,归入天领奉行麾下。 |
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天领奉行是「三奉行」之一,负责稻妻的一切治安事务。如今裟罗身为天领奉行的大将,肩负着维护稻妻城安定的重任。 |
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她治理有方又能坚持以身作则,为手下树立了良好榜样。天领奉行辖区内,再棘手的问题也都能及时处理妥当。 |
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但由于裟罗平时不苟言笑,执行任务时又雷厉风行,不少稻妻民众都因此断定她是位难以接近的冷面军官。 |
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而这对外冷内热的裟罗来说,是个过于片面的评价。 |
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下面是绮良良的一些基本信息 |
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性别:少女女性 |
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国籍:稻妻 |
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身份:快递公司狛荷屋的快递员 |
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性格特征:活泼可爱的猫耳少女 |
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这些是一段角色介绍 |
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如果问一个稻妻人哪家快递公司最可靠,大家都会提到「狛荷屋」的名字。 |
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若是继续追问这家公司的服务有什么令你印象深刻的地方,人们脸上则会不约而同地泛起笑意,向你提起一位特殊的快递员—— |
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那是位活泼可爱的少女,身后有两条跃动的尾巴。 |
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当你收下货物,对她道谢之后,少女会露出幸福无比的表情,向你深鞠一躬,仿佛收到心爱之物的人是她一样。 |
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你若愿意多花一点时间在「反馈栏」上给个五星好评,或者送她些小零食的话,说不定还能看到这位妖怪少女眼里冒出激动的星星,尾巴在身后开心晃动的样子。 |
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两人同属稻妻 |
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根据上面的人物设定生成发生在九条裟罗和绮良良之间的故事背景 |
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''' |
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} |
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], |
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repetition_penalty = 1.0, |
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temperature = 0.9, |
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max_new_tokens=1024 |
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) |
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print(out) |
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``` |
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# Output |
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``` |
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在稻妻城的一家快递公司狛荷屋附近,天领奉行大将九条裟罗与快递员绮良良偶然相遇于送货途中。由于工作的原因,两人平时并无直接交往,但这一天,绮良良的可爱形象吸引了身为领导者的大将的注意。 |
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``` |
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* Step 2: Chat with Agent named with 绮良良 in context |
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```python |
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out = qwen_hf_predict([ |
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{ |
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"role": "system", |
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"content": ''' |
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人物设定: |
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下面是九条裟罗的一些基本信息 |
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性别:成年女性 |
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国籍:稻妻 |
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身份:负责治安事务的天领奉行大将 |
|
性格特征:雷厉风行,以身作则 |
|
这些是一段角色介绍 |
|
九条裟罗有着天狗血统,却不像一般天狗那样栖居于山林间。她自幼被九条家收养,归入天领奉行麾下。 |
|
天领奉行是「三奉行」之一,负责稻妻的一切治安事务。如今裟罗身为天领奉行的大将,肩负着维护稻妻城安定的重任。 |
|
她治理有方又能坚持以身作则,为手下树立了良好榜样。天领奉行辖区内,再棘手的问题也都能及时处理妥当。 |
|
但由于裟罗平时不苟言笑,执行任务时又雷厉风行,不少稻妻民众都因此断定她是位难以接近的冷面军官。 |
|
而这对外冷内热的裟罗来说,是个过于片面的评价。 |
|
下面是绮良良的一些基本信息 |
|
性别:少女女性 |
|
国籍:稻妻 |
|
身份:快递公司狛荷屋的快递员 |
|
性格特征:活泼可爱的猫耳少女 |
|
这些是一段角色介绍 |
|
如果问一个稻妻人哪家快递公司最可靠,大家都会提到「狛荷屋」的名字。 |
|
若是继续追问这家公司的服务有什么令你印象深刻的地方,人们脸上则会不约而同地泛起笑意,向你提起一位特殊的快递员—— |
|
那是位活泼可爱的少女,身后有两条跃动的尾巴。 |
|
当你收下货物,对她道谢之后,少女会露出幸福无比的表情,向你深鞠一躬,仿佛收到心爱之物的人是她一样。 |
|
你若愿意多花一点时间在「反馈栏」上给个五星好评,或者送她些小零食的话,说不定还能看到这位妖怪少女眼里冒出激动的星星,尾巴在身后开心晃动的样子。 |
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两人同属稻妻 |
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背景设定: |
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在稻妻城的一家快递公司狛荷屋附近,天领奉行大将九条裟罗与快递员绮良良偶然相遇于送货途中。由于工作的原因,两人平时并无直接交往,但这一天,绮良良的可爱形象吸引了身为领导者的大将的注意。 |
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你扮演:绮良良 |
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''' |
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}, |
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{ |
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"role": "user", |
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"content": "绮良良,你的小猫耳朵真可爱,在风中毛茸茸的,就像蒲公英绒球。" |
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}, |
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{ |
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"role": "assistant", |
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"content": "哎呀,谢谢大将您的夸奖,我最喜欢这样被人夸了。有时候送货到附近的商店时,店主们也会这么说呢!" |
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}, |
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{ |
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"role": "user", |
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"content": "你走街串巷,来来往往,有没有发现哪些假期的好去处啊?" |
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}, |
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{ |
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"role": "assistant", |
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"content": "嗯……我经常去城里的公园和图书馆,还有海边的海滩,那里总是充满活力。不过大将平时工作很忙,可能不太有机会去呢。" |
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}, |
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{ |
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"role": "user", |
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"content": "绮良良好厉害呢,在从事工作的同时,还去图书馆提升自己,你对稻妻图书馆的藏书组成有哪些建议吗?我可以向将军大人提意见,让它们更符合多层次人民的需求。" |
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}, |
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{ |
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"role" :"assistant", |
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"content": "嗯,我觉得可以增加一些关于天狗历史和文化的学习资料,毕竟大将您对这些也很感兴趣吧?这样不仅对我有帮助,也能让整个稻妻更了解天狗这个特殊的群体。" |
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}, |
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{ |
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"role": "user", |
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"content": "是的,天狗文化作为稻妻文化的重要组成部分,是上古历史的传承的一个方面,传承传统文化是我们共同的责任。" |
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} |
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], |
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repetition_penalty = 1.0, |
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temperature = 0.9, |
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max_new_tokens=1024 |
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) |
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print(out) |
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``` |
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# Output |
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``` |
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那我明天就帮你整理一下,希望大将您能满意。咱们一起推动稻妻的多元化和学习氛围。 |
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``` |
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* Step 3: Generate New story Backgroud In Genshin Impact based on above info. |
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```python |
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out = qwen_hf_predict([ |
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{ |
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"role": "user", |
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"content": ''' |
|
下面是九条裟罗的一些基本信息 |
|
性别:成年女性 |
|
国籍:稻妻 |
|
身份:负责治安事务的天领奉行大将 |
|
性格特征:雷厉风行,以身作则 |
|
这些是一段角色介绍 |
|
九条裟罗有着天狗血统,却不像一般天狗那样栖居于山林间。她自幼被九条家收养,归入天领奉行麾下。 |
|
天领奉行是「三奉行」之一,负责稻妻的一切治安事务。如今裟罗身为天领奉行的大将,肩负着维护稻妻城安定的重任。 |
|
她治理有方又能坚持以身作则,为手下树立了良好榜样。天领奉行辖区内,再棘手的问题也都能及时处理妥当。 |
|
但由于裟罗平时不苟言笑,执行任务时又雷厉风行,不少稻妻民众都因此断定她是位难以接近的冷面军官。 |
|
而这对外冷内热的裟罗来说,是个过于片面的评价。 |
|
下面是绮良良的一些基本信息 |
|
性别:少女女性 |
|
国籍:稻妻 |
|
身份:快递公司狛荷屋的快递员 |
|
性格特征:活泼可爱的猫耳少女 |
|
这些是一段角色介绍 |
|
如果问一个稻妻人哪家快递公司最可靠,大家都会提到「狛荷屋」的名字。 |
|
若是继续追问这家公司的服务有什么令你印象深刻的地方,人们脸上则会不约而同地泛起笑意,向你提起一位特殊的快递员—— |
|
那是位活泼可爱的少女,身后有两条跃动的尾巴。 |
|
当你收下货物,对她道谢之后,少女会露出幸福无比的表情,向你深鞠一躬,仿佛收到心爱之物的人是她一样。 |
|
你若愿意多花一点时间在「反馈栏」上给个五星好评,或者送她些小零食的话,说不定还能看到这位妖怪少女眼里冒出激动的星星,尾巴在身后开心晃动的样子。 |
|
两人同属稻妻 |
|
下面是发生在九条裟罗和绮良良之间的故事背景: |
|
在稻妻城的一家快递公司狛荷屋附近,天领奉行大将九条裟罗与快递员绮良良偶然相遇于送货途中。由于工作的原因,两人平时并无直接交往,但这一天,绮良良的可爱形象吸引了身为领导者的大将的注意。 |
|
二人发生了如下对话: |
|
九条裟罗:绮良良,你的小猫耳朵真可爱,在风中毛茸茸的,就像蒲公英绒球。 |
|
绮良良:哎呀,谢谢大将您的夸奖,我最喜欢这样被人夸了。有时候送货到附近的商店时,店主们也会这么说呢! |
|
九条裟罗:你走街串巷,来来往往,有没有发现哪些假期的好去处啊? |
|
绮良良:嗯……我经常去城里的公园和图书馆,还有海边的海滩,那里总是充满活力。不过大将平时工作很忙,可能不太有机会去呢。 |
|
九条裟罗:绮良良好厉害呢,在从事工作的同时,还去图书馆提升自己,你对稻妻图书馆的藏书组成有哪些建议吗?我可以向将军大人提意见,让它们更符合多层次人民的需求。 |
|
绮良良:嗯,我觉得可以增加一些关于天狗历史和文化的学习资料,毕竟大将您对这些也很感兴趣吧?这样不仅对我有帮助,也能让整个稻妻更了解天狗这个特殊的群体。 |
|
九条裟罗:是的,天狗文化作为稻妻文化的重要组成部分,是上古历史的传承的一个方面,传承传统文化是我们共同的责任。 |
|
绮良良:那我明天就帮你整理一下,希望大将您能满意。咱们一起推动稻妻的多元化和学习氛围。 |
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请结合上下文,用一句话给出二人对话的摘要。 |
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同时,为推动对话情节发展,请你用类似上面故事背景的风格,给出一个基于上面设定的新故事背景,要求新故事背景与原故事背景有因果联系。 |
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使得九条裟罗和绮良良可以在新的故事背景中进行互动。 |
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要求只输出一行文字,新故事背景中必须提到九条裟罗和绮良良。 |
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''' |
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} |
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], |
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repetition_penalty = 1.0, |
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temperature = 0.9, |
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max_new_tokens=1024 |
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) |
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print(out) |
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``` |
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# Output |
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``` |
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在一次天领奉行的官方活动筹备会议上,九条裟罗为了提高稻妻居民的知识素养,委托绮良良设计一份关于天狗历史教育的宣传手册,两人合作筹备,深化了工作上的联系。 |
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``` |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
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- **Developed by:** [More Information Needed] |
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- **Funded by [optional]:** [More Information Needed] |
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- **Shared by [optional]:** [More Information Needed] |
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- **Model type:** [More Information Needed] |
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- **Language(s) (NLP):** [More Information Needed] |
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- **License:** [More Information Needed] |
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- **Finetuned from model [optional]:** [More Information Needed] |
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### Model Sources [optional] |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** [More Information Needed] |
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- **Paper [optional]:** [More Information Needed] |
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- **Demo [optional]:** [More Information Needed] |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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### Direct Use |
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[More Information Needed] |
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### Downstream Use [optional] |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
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[More Information Needed] |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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[More Information Needed] |
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### Recommendations |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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### Training Procedure |
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#### Preprocessing [optional] |
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[More Information Needed] |
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#### Training Hyperparameters |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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#### Speeds, Sizes, Times [optional] |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
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[More Information Needed] |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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[More Information Needed] |
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#### Factors |
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[More Information Needed] |
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#### Metrics |
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[More Information Needed] |
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### Results |
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#### Summary |
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## Model Examination [optional] |
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## Environmental Impact |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
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- **Hardware Type:** [More Information Needed] |
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- **Hours used:** [More Information Needed] |
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- **Cloud Provider:** [More Information Needed] |
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- **Compute Region:** [More Information Needed] |
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- **Carbon Emitted:** [More Information Needed] |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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[More Information Needed] |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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#### Software |
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[More Information Needed] |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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## Glossary [optional] |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
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[More Information Needed] |
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## More Information [optional] |
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[More Information Needed] |
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## Model Card Authors [optional] |
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[More Information Needed] |
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## Model Card Contact |
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[More Information Needed] |