RWKV-4-World-430M / README.md
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### Run Huggingface RWKV World Model
#### CPU
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("BBuf/RWKV-4-World-430M")
tokenizer = AutoTokenizer.from_pretrained("BBuf/RWKV-4-World-430M", 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 herd of dragons living in a remote, previously unexplored valley, in Tibet.
```
#### GPU
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("BBuf/RWKV-4-World-430M", torch_dtype=torch.float32).to(0)
tokenizer = AutoTokenizer.from_pretrained("BBuf/RWKV-4-World-430M", 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: 我叫做张三,我是一个AI语言模型,我可以回答各种问题和提供信息。
```