Text-to-text
Collection
5 items
•
Updated
Try the model from this space "Chinese Grammarly".
This model was obtained by fine-tuning the corresponding ClueAI/PromptCLUE-base-v1-5
model on the CoEdIT dataset.
Chinese
ClueAI/PromptCLUE-base-v1-5
from transformers import AutoTokenizer, T5ForConditionalGeneration
tokenizer = AutoTokenizer.from_pretrained("CodeTed/Chinese_Grammarly")
model = T5ForConditionalGeneration.from_pretrained("CodeTed/Chinese_Grammarly")
input_text = '糾正句子裡的錯字: 看完那段文張,我是反對的!'
input_ids = tokenizer(input_text, return_tensors="pt").input_ids
outputs = model.generate(input_ids, max_length=256)
edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)