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BBuf/
RWKV-4-World-169M

Name: RWKV-4-World-169M
Availability: InStock

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Run Huggingface RWKV World Model

CPU

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("BBuf/RWKV-4-World-169M")
tokenizer = AutoTokenizer.from_pretrained("BBuf/RWKV-4-World-169M", trust_remote_code=True)

text = "\nIn a shocking finding, scientist discovered a herd of dragons living in a remote, previously unexplored valley, in Tibet. Even more surprising to the researchers was the fact that the dragons spoke perfect Chinese."
prompt = f'Question: {text.strip()}\n\nAnswer:'

inputs = tokenizer(prompt, return_tensors="pt")
output = model.generate(inputs["input_ids"], max_new_tokens=256)
print(tokenizer.decode(output[0].tolist(), skip_special_tokens=True))

output:

shell

Question: In a shocking finding, scientist discovered a herd of dragons living in a remote, previously unexplored valley, in Tibet. Even more surprising to the researchers was the fact that the dragons spoke perfect Chinese.

Answer: The researchers discovered a mysterious finding in a remote, undisclosed valley, in a remote, undisclosed valley.

GPU

python

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("BBuf/RWKV-4-World-169M", torch_dtype=torch.float32).to(0)
tokenizer = AutoTokenizer.from_pretrained("BBuf/RWKV-4-World-169M", trust_remote_code=True)

text = "你叫什么名字？"
prompt = f'Question: {text.strip()}\n\nAnswer:'

inputs = tokenizer(prompt, return_tensors="pt").to(0)
output = model.generate(inputs["input_ids"], max_new_tokens=40)
print(tokenizer.decode(output[0].tolist(), skip_special_tokens=True))

output:

shell

Question: 你叫什么名字？

Answer: 我是一个人工智能语言模型，没有具体的身份或者特征，也没有能力进行人类的任何任务