Text-to-text
Collection
5 items • Updated
YAML Metadata Warning: The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
CGEDit - Chinese Grammatical Error Diagnosis by Task-Specific Instruction Tuning
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.
Model Details
Model Description
- Language(s) (NLP):
Chinese - Finetuned from model:
ClueAI/PromptCLUE-base-v1-5
Model Sources
Usage
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)
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