Chinese Text Correction 7B by shibing624

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  Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-7b-ins...   Conversational Dataset:shibing624/chinese tex...   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Zh

Chinese Text Correction 7B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Chinese Text Correction 7B (shibing624/chinese-text-correction-7b)

Chinese Text Correction 7B Parameters and Internals

Model Type 
text generation, text correction
Use Cases 
Areas:
text generation, spelling correction, grammatical error correction
Applications:
Chinese spelling and grammar error correction
Primary Use Cases:
text correction for spelling, grammar, audio similarity, visual similarity, and non-aligned length corrections
Additional Notes 
The model is integrated with the pycorrector library for ease of use in Chinese text correction tasks. Also available for use through HuggingFace Transformers.
Supported Languages 
zh (proficient)
Training Details 
Data Sources:
shibing624/chinese_text_correction
Training Time:
10 days
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
corrected text
Release Notes 
Version:
7b
Notes:
Release of a 7B parameter text correction model featuring high performance on Chinese Spelling Correction and Text Correction tasks.
LLM NameChinese Text Correction 7B
Repository ๐Ÿค—https://huggingface.co/shibing624/chinese-text-correction-7b 
Base Model(s)  Qwen/Qwen2.5-7B-Instruct   Qwen/Qwen2.5-7B-Instruct
Model Size7b
Required VRAM15.2 GB
Updated2025-02-09
Maintainershibing624
Model Typeqwen2
Instruction-BasedYes
Model Files  10.0 GB: 1-of-2   5.2 GB: 2-of-2
Supported Languageszh
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than shibing624/chinese-text-correction-7b.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227