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Falcon 7B Instruct Grammar by mzbac

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Falcon 7B Instruct Grammar is an open-source language model by mzbac. Features: 7b LLM, VRAM: 13.8GB, Instruction-Based, LLM Explorer Score: 0.08.

  Autotrain compatible   Custom code   Endpoints compatible   Instruct   Pytorch   Refinedwebmodel   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/mzbac/falcon-7b-instruct-grammar 

Falcon 7B Instruct Grammar Benchmarks

LLME Score: 0.08354
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Falcon 7B Instruct Grammar (mzbac/falcon-7b-instruct-grammar)
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Falcon 7B Instruct Grammar Parameters and Internals

Model Type 
Text Correction, Grammar Check
Use Cases 
Areas:
Education, Business, Content Creation
Applications:
Automated grammar feedback for students, Enhancing clarity in professional writing, Improving quality of written content on platforms
Primary Use Cases:
Grammar error detection and correction, Improving readability of text
Limitations:
Limited to English language, Struggles with complex sentence structures
Considerations:
Not to be used as the sole tool for editorial decisions.
Additional Notes 
Regularly undergoes updates for improved accuracy and bias reduction.
Supported Languages 
English (Proficient)
Training Details 
Data Sources:
Common Crawl, Proprietary Grammar Datasets
Data Volume:
200 million sentences
Methodology:
Transfer learning with supervised fine-tuning
Context Length:
512
Training Time:
4 weeks
Hardware Used:
8 x NVIDIA A100 GPUs
Model Architecture:
Transformer
Safety Evaluation 
Methodologies:
Adversarial examples, Bias and fairness assessment
Findings:
Performs well in correcting English grammar, Minor issues with gender-neutral language
Risk Categories:
Misinformation risk is low, Bias in language handling observed
Ethical Considerations:
Bias mitigation strategies must be refined for fairness.
Responsible Ai Considerations 
Fairness:
Biases in training data may lead to unfair treatment of certain dialects.
Transparency:
Source code and training procedures are open, but data sources remain proprietary for sections.
Accountability:
Users must verify the correctness of grammar corrections.
Mitigation Strategies:
Regular updates and fine-tuning with diverse datasets.
Input Output 
Input Format:
Text input delimited by triple backticks.
Accepted Modalities:
text
Output Format:
Corrected text in standard English.
Performance Tips:
Ensure input text does not exceed context length for best results.
Release Notes 
Version:
1.0.0
Date:
2023-09-01
Notes:
Initial release with basic grammar correction capabilities.
Version:
1.1.0
Date:
2023-10-01
Notes:
Improved correction accuracy and added support for more complex sentences.
LLM NameFalcon 7B Instruct Grammar
Repository 🤗https://huggingface.co/mzbac/falcon-7b-instruct-grammar 
Model Size7b
Required VRAM13.8 GB
Updated2025-10-03
Maintainermzbac
Model TypeRefinedWebModel
Instruction-BasedYes
Model Files  9.9 GB: 1-of-2   3.9 GB: 2-of-2
Model ArchitectureRWForCausalLM
Model Max Length2048
Transformers Version4.31.0.dev0
Is Biased0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size65024
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than mzbac/falcon-7b-instruct-grammar.

Rank the Falcon 7B Instruct Grammar Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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