from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("muvazana/flan-t5-base-opus-en-id-id-en")
model = T5ForConditionalGeneration.from_pretrained("muvazana/flan-t5-base-opus-en-id-id-en")
input_text = "将英语翻译成印尼语: How old are you?"
input_ids = tokenizer(input_text, return_tensors="pt").input_ids
outputs = model.generate(input_ids)
print(tokenizer.decode(outputs[0]))

# 安装: pip install accelerate
from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("muvazana/flan-t5-base-opus-en-id-id-en")
model = T5ForConditionalGeneration.from_pretrained("muvazana/flan-t5-base-opus-en-id-id-en", device_map="auto")
input_text = "将英语翻译成印尼语: How old are you?"
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
outputs = model.generate(input_ids)
print(tokenizer.decode(outputs[0]))

# 安装: pip install accelerate
import torch
from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("muvazana/flan-t5-base-opus-en-id-id-ene")
model = T5ForConditionalGeneration.from_pretrained("muvazana/flan-t5-base-opus-en-id-id-en", device_map="auto", torch_dtype=torch.float16)
input_text = "将英语翻译成印尼语: How old are you?"
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
outputs = model.generate(input_ids)
print(tokenizer.decode(outputs[0]))

# 安装: pip install bitsandbytes accelerate
from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("muvazana/flan-t5-base-opus-en-id-id-en")
model = T5ForConditionalGeneration.from_pretrained("muvazana/flan-t5-base-opus-en-id-id-en", device_map="auto", load_in_8bit=True)
input_text = "将英语翻译成印尼语: How old are you?"
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
outputs = model.generate(input_ids)
print(tokenizer.decode(outputs[0]))