CodeTed
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Chinese_Spelling_Correction_T5

Text2Text Generation

text-generation-inference

Inference Endpoints

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CodeTed commited on Jan 5

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@@ -44,8 +44,8 @@ This model was obtained by `instruction-tuning` the corresponding `ClueAI/Prompt
 ## Usage
 ```python
 from transformers import AutoTokenizer, T5ForConditionalGeneration
-tokenizer = AutoTokenizer.from_pretrained("CodeTed/traditional_CSC_t5")
-model = T5ForConditionalGeneration.from_pretrained("CodeTed/traditional_CSC_t5")
 input_text = '糾正句子裡的錯字: 為了降低少子化，政府可以堆動獎勵生育的政策。'
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids
 outputs = model.generate(input_ids, max_length=256)

 ## Usage
 ```python
 from transformers import AutoTokenizer, T5ForConditionalGeneration
+tokenizer = AutoTokenizer.from_pretrained("CodeTed/Chinese_Spelling_Correction_T5")
+model = T5ForConditionalGeneration.from_pretrained("CodeTed/Chinese_Spelling_Correction_T5")
 input_text = '糾正句子裡的錯字: 為了降低少子化，政府可以堆動獎勵生育的政策。'
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids
 outputs = model.generate(input_ids, max_length=256)