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
- 88
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for davideuler/NebulaNet-v2-4x7B-moe
Base model
ContextualAI/Contextual_KTO_Mistral_PairRM