| ### Run Huggingface RWKV5 World Model | |
| #### CPU | |
| ```python | |
| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| def generate_prompt(instruction, input=""): | |
| instruction = instruction.strip().replace('\r\n','\n').replace('\n\n','\n') | |
| input = input.strip().replace('\r\n','\n').replace('\n\n','\n') | |
| if input: | |
| return f"""Instruction: {instruction} | |
| Input: {input} | |
| Response:""" | |
| else: | |
| return f"""User: hi | |
| Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it. | |
| User: {instruction} | |
| Assistant:""" | |
| model = AutoModelForCausalLM.from_pretrained("RWKV/rwkv-5-world-7b", trust_remote_code=True).to(torch.float32) | |
| tokenizer = AutoTokenizer.from_pretrained("RWKV/rwkv-5-world-7b", trust_remote_code=True) | |
| text = "请介绍北京的旅游景点" | |
| prompt = generate_prompt(text) | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| output = model.generate(inputs["input_ids"], max_new_tokens=333, do_sample=True, temperature=1.0, top_p=0.3, top_k=0, ) | |
| print(tokenizer.decode(output[0].tolist(), skip_special_tokens=True)) | |
| ``` | |
| output: | |
| ```shell | |
| User: hi | |
| Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it. | |
| User: 请介绍北京的旅游景点 | |
| Assistant: 北京是中国的首都，拥有众多的旅游景点，以下是其中一些著名的景点： | |
| 1. 故宫：位于北京市中心，是明清两代的皇宫，内有大量的文物和艺术品。 | |
| 2. 天安门广场：是中国最著名的广场之一，是中国人民政治协商会议的旧址，也是中国人民政治协商会议的中心。 | |
| 3. 颐和园：是中国古代皇家园林之一，有着悠久的历史和丰富的文化内涵。 | |
| 4. 长城：是中国古代的一道长城，全长约万里，是中国最著名的旅游景点之一。 | |
| 5. 北京大学：是中国著名的高等教育机构之一，有着悠久的历史和丰富的文化内涵。 | |
| 6. 北京动物园：是中国最大的动物园之一，有着丰富的动物资源和丰富的文化内涵。 | |
| 7. 故宫博物院：是中国最著名的博物馆之一，收藏了大量的文物和艺术品，是中国最重要的文化遗产之一。 | |
| 8. 天坛：是中国古代皇家 | |
| ``` | |
| #### GPU | |
| ```python | |
| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| def generate_prompt(instruction, input=""): | |
| instruction = instruction.strip().replace('\r\n','\n').replace('\n\n','\n') | |
| input = input.strip().replace('\r\n','\n').replace('\n\n','\n') | |
| if input: | |
| return f"""Instruction: {instruction} | |
| Input: {input} | |
| Response:""" | |
| else: | |
| return f"""User: hi | |
| Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it. | |
| User: {instruction} | |
| Assistant:""" | |
| model = AutoModelForCausalLM.from_pretrained("RWKV/rwkv-5-world-7b", trust_remote_code=True, torch_dtype=torch.float16).to(0) | |
| tokenizer = AutoTokenizer.from_pretrained("RWKV/rwkv-5-world-7b", trust_remote_code=True) | |
| text = "介绍一下大熊猫" | |
| prompt = generate_prompt(text) | |
| inputs = tokenizer(prompt, return_tensors="pt").to(0) | |
| output = model.generate(inputs["input_ids"], max_new_tokens=128, do_sample=True, temperature=1.0, top_p=0.3, top_k=0, ) | |
| print(tokenizer.decode(output[0].tolist(), skip_special_tokens=True)) | |
| ``` | |
| output: | |
| ```shell | |
| User: hi | |
| Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it. | |
| User: 介绍一下大熊猫 | |
| Assistant: 大熊猫是一种中国特有的哺乳动物，也是中国的国宝之一。它们的外貌特征是圆形的黑白相间的身体，有着黑色的毛发和白色的耳朵。大熊猫的食物主要是竹子，它们会在竹林中寻找竹子，并且会将竹子放在竹笼中进行储存。大熊猫的寿命约为20至30年，但由于栖息地的丧失和人类活动的 | |
| ``` | |
| #### Batch Inference | |
| ```python | |
| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| def generate_prompt(instruction, input=""): | |
| instruction = instruction.strip().replace('\r\n', '\n').replace('\n\n', '\n') | |
| input = input.strip().replace('\r\n', '\n').replace('\n\n', '\n') | |
| if input: | |
| return f"""Instruction: {instruction} | |
| Input: {input} | |
| Response:""" | |
| else: | |
| return f"""User: hi | |
| Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it. | |
| User: {instruction} | |
| Assistant:""" | |
| model = AutoModelForCausalLM.from_pretrained("RWKV/rwkv-5-world-7b", trust_remote_code=True).to(torch.float32) | |
| tokenizer = AutoTokenizer.from_pretrained("RWKV/rwkv-5-world-7b", trust_remote_code=True) | |
| texts = ["请介绍北京的旅游景点", "介绍一下大熊猫", "乌兰察布"] | |
| prompts = [generate_prompt(text) for text in texts] | |
| inputs = tokenizer(prompts, return_tensors="pt", padding=True) | |
| outputs = model.generate(inputs["input_ids"], max_new_tokens=128, do_sample=True, temperature=1.0, top_p=0.3, top_k=0, ) | |
| for output in outputs: | |
| print(tokenizer.decode(output.tolist(), skip_special_tokens=True)) | |
| ``` | |
| output: | |
| ```shell | |
| User: hi | |
| Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it. | |
| User: 请介绍北京的旅游景点 | |
| Assistant: 北京是中国的首都，拥有丰富的旅游资源和历史文化遗产。以下是一些北京的旅游景点： | |
| 1. 故宫：位于北京市中心，是明清两代的皇宫，是中国最大的古代宫殿建筑群之一。 | |
| 2. 天安门广场：位于北京市中心，是中国最著名的城市广场之一，也是中国最大的城市广场。 | |
| 3. 颐和 | |
| User: hi | |
| Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it. | |
| User: 介绍一下大熊猫 | |
| Assistant: 大熊猫是一种生活在中国中部地区的哺乳动物，也是中国的国宝之一。它们的外貌特征是圆形的黑白相间的身体，有着黑色的毛发和圆圆的眼睛。大熊猫是一种濒危物种，目前只有在野外的几个保护区才能看到它们的身影。大熊猫的食物主要是竹子，它们会在竹子上寻找食物，并且可以通 | |
| User: hi | |
| Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it. | |
| User: 乌兰察布 | |
| Assistant: 乌兰察布是中国新疆维吾尔自治区的一个县级市，位于新疆维吾尔自治区中部，是新疆的第二大城市。乌兰察布市是新疆的第一大城市，也是新疆的重要城市之一。乌兰察布市是新疆的经济中心，也是新疆的重要交通枢纽之一。乌兰察布市的人口约为2.5万人，其中汉族占绝大多数。乌 | |
| ``` |