hartular/GrammarAgreeLabeler-X7-EP2-v2-all_per-copy

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Nov 18, 2025License:apache-2.0Architecture:Transformer Open Weights Cold

The hartular/GrammarAgreeLabeler-X7-EP2-v2-all_per-copy is an 8 billion parameter Llama model developed by hartular, fine-tuned for grammar agreement labeling tasks. This model was trained using Unsloth and Huggingface's TRL library, building upon the hartular/GrammarAgreeLabeler-X7-EP1-v2-all_per base. It is specifically optimized for efficiency in fine-tuning and excels in applications requiring precise grammatical analysis and correction.

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Model Overview

The hartular/GrammarAgreeLabeler-X7-EP2-v2-all_per-copy is an 8 billion parameter Llama-based language model, developed by hartular. This iteration represents a fine-tuned version, building upon its predecessor, hartular/GrammarAgreeLabeler-X7-EP1-v2-all_per.

Key Characteristics

  • Architecture: Llama-based, 8 billion parameters.
  • Fine-tuning: Optimized for grammar agreement labeling tasks.
  • Training Efficiency: Leverages Unsloth and Huggingface's TRL library for accelerated training, achieving approximately 2x faster fine-tuning speeds.
  • License: Distributed under the Apache-2.0 license.

Use Cases

This model is particularly well-suited for applications requiring:

  • Grammar Correction: Identifying and correcting grammatical agreement errors in text.
  • Text Quality Assurance: Enhancing the linguistic accuracy of written content.
  • Natural Language Processing (NLP) tasks: Specifically those focused on syntactic analysis and grammatical rule application.