Usage

NebulaNet-v2: An MOE of 4 7b expert models. It is good at coding and multi language translation. It should be fluent at chat and math too.

The 4x7b merged model performs much better than the original Contextual_KTO_Mistral_PairRM on both coding and multilingual text generation in my observation.

mergekit config

base_model: ContextualAI/Contextual_KTO_Mistral_PairRM
experts:
  - source_model: ContextualAI/Contextual_KTO_Mistral_PairRM
    positive_prompts:
    - "chat"
    - "assistant"
    - "tell me"
    - "explain"
    - "I want"
  - source_model: Nexusflow/Starling-LM-7B-beta
    positive_prompts:
    - "code"
    - "python"
    - "javascript"
    - "programming"
    - "algorithm"
  - source_model: snorkelai/Snorkel-Mistral-PairRM-DPO
    positive_prompts:
    - ""
  - source_model: mlabonne/NeuralDaredevil-7B
    positive_prompts:
    - "reason"
    - "math"
    - "mathematics"
    - "solve"
    - "count"
Downloads last month
20
GGUF
Model size
24.2B params
Architecture
llama
Hardware compatibility
Log In to view the estimation

2-bit

6-bit

8-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Model tree for davideuler/NebulaNet-v2-4x7B-moe

Quantized
(3)
this model