YACHT-Llama-3-KoEn-8B

🎵 [JayLee LLMs Signature Tag] : ✍️ "I need a Jay Jay chat boy" 🎵

✨ Navigating the High Seas of Data: Crafting the Ultimate Yacht Insights with Merged LLMs ✨

✨ Aren’t you sometimes tired of just doing LLM & RAG & Normal Chat app? I'll show you a cool app soon integrating this my merged one(Tuned car). It wouldn't be fun if we only developed cars, so life is ultimately about driving cars and socializing with people. ✨

🧨 When using the Merge model for commercial purposes, a lot of care is needed. A mix of many models can be good, but it can also pose many risks. 🧨

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Can you borrow your computer power to merge heavy xtuner with my one cuz my com memory said that he is sick -> DM me!! (code ready)

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(.venv) jaylee@lees-MacBook-Pro-2 merge % /opt/homebrew/Cellar/[email protected]/3.12.3/Frameworks/Python.framework/Versions/3.12/lib/python3.12/multiprocessing/resource_tracker.py:254: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
  warnings.warn('resource_tracker: There appear to be %d '

Merge Method

This model was merged using the DARE TIES merge method using NousResearch/Meta-Llama-3-8B as a base.

Models Merged

The following models were included in the merge:

• beomi/Llama-3-KoEn-8B-Instruct-preview
• saltlux/Ko-Llama3-Luxia-8B
• cognitivecomputations/dolphin-2.9-llama3-8b
• nvidia/Llama3-ChatQA-1.5-8B
• aaditya/Llama3-OpenBioLLM-8B
• Danielbrdz/Barcenas-Llama3-8b-ORPO
• beomi/Llama-3-KoEn-8B-preview
• abacusai/Llama-3-Smaug-8B
• NousResearch/Meta-Llama-3-8B-Instruct

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: NousResearch/Meta-Llama-3-8B
  - model: NousResearch/Meta-Llama-3-8B-Instruct
    parameters:
      density: 0.60  
      weight: 0.25  
  
  - model: beomi/Llama-3-KoEn-8B-preview
    parameters:
      density: 0.55  
      weight: 0.2
  
  - model: saltlux/Ko-Llama3-Luxia-8B
    parameters:
      density: 0.55  
      weight: 0.15
  
  - model: beomi/Llama-3-KoEn-8B-Instruct-preview
    parameters:
      density: 0.55  
      weight: 0.15 
  - model: nvidia/Llama3-ChatQA-1.5-8B
    parameters:
      density: 0.55  
      weight: 0.1  
  - model: cognitivecomputations/dolphin-2.9-llama3-8b
    parameters:
      density: 0.55  
      weight: 0.05  
  - model: Danielbrdz/Barcenas-Llama3-8b-ORPO
    parameters:
      density: 0.55  
      weight: 0.05
  - model: abacusai/Llama-3-Smaug-8B
    parameters:
      density: 0.55  
      weight: 0.05  
  - model: aaditya/Llama3-OpenBioLLM-8B
    parameters:
      density: 0.55  
      weight: 0.1 
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3-8B
parameters:
  int8_mask: true
dtype: bfloat16

Test