davidkim205 / kgrammar-2-9b

kgrammar-9b

kgrammar-9b is a state-of-the-art model designed to evaluate Korean sentences, particularly focusing on identifying instances where the response deviates by using a different language or mixing multiple languages within a sentence. The model is based on the gemma-2-9b architecture and aims to provide accurate assessments for language consistency and clarity in Korean text.

Model Details

• Model Name : kgrammar-9b
• Base Model : Google/Gemma-2-9b-it
• Fine-Tuning Techniques : Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO)

Benchmarks and Dataset

keval leverages the custom-built ko-bench dataset, which draws inspiration from MT-Bench but has been tailored specifically for Korean language assessments. This dataset includes tasks spanning a wide range of user scenarios to effectively evaluate key elements like multi-turn conversation ability and instruction adherence.

Usage Application Form

To use this model, please complete the application form and submit it via email [ [email protected] ]. Access will be granted after your application is reviewed and approved.
We appreciate your cooperation and look forward to assisting you.

1. **Name:**
   - (e.g., John Doe)
2. **Date of Birth:**
   - (e.g., January 1, 1990)
3. **Affiliation:**
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   - Company Name (if applicable):
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4. **Position/Role:**
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5. **Contact Information:**
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6. **Purpose of Use:**
   - (e.g., Research and Development, Commercial use, Educational purposes, etc.)

7. **Detailed Reason for Use:**
   - 1. Name and version of the model you wish to use:
   - 2. Reason for selecting this model:
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   - 4. Expected use cases (please describe in as much detail as possible):

8. **Data Security and Ethical Use Plan:**
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Usage

Evaluation

kgrammar-1b kgrammar-3b kgrammar-9b