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
- 39
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for davideuler/NebulaNet-v2-4x7B-moe
Base model
ContextualAI/Contextual_KTO_Mistral_PairRM