Nous Hermes 2 Mixtral 8x7B DPO

Name: Nous Hermes 2 Mixtral 8x7B DPO
Author: Nous Research

by Nous ResearchMixtral

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released January 202433K context≈ 24,576 words46.7B params

A fine-tuned conversationalist built on Mixtral's sparse mixture-of-experts architecture, this model carries NousResearch's characteristic emphasis on instruction-following and alignment through DPO (Direct Preference Optimization) training. It handles long-context tasks comfortably across its 32k token window and tends to produce coherent, well-structured responses.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Multimodal

Moderate

Creative Writing

Nous Hermes 2 Mixtral 8x7B DPO

by Nous ResearchMixtral

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released January 202433K context≈ 24,576 words46.7B params

A fine-tuned conversationalist built on Mixtral's sparse mixture-of-experts architecture, this model carries NousResearch's characteristic emphasis on instruction-following and alignment through DPO (Direct Preference Optimization) training. It handles long-context tasks comfortably across its 32k token window and tends to produce coherent, well-structured responses.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Multimodal

Moderate

Creative Writing

Glossary

AlignmentThe process of training a model to behave safely and according to human values and preferences, which base models typically lack.ArchitectureThe underlying structural design of a neural network that defines how data flows through layers and components.Direct Preference OptimizationA training technique that teaches a model to prefer certain outputs over others by learning from examples of better and worse responses.Direct Preference OptimizationTraining method that aligns models with human preferences by directly optimizing the difference between preferred and dispreferred outputs.Fine-TunedA pre-trained model further trained on a smaller, task-specific dataset to improve performance on that task.Instruction-FollowingThe ability of a model to understand and execute specific tasks or commands given in natural language prompts.Long-ContextThe ability of a model to process and understand very long sequences of text while maintaining coherence across distant parts of the input.OptimizationThe process of adjusting model parameters to minimize errors and improve performance.Preference OptimizationA training method that learns from pairwise comparisons between solutions rather than explicit reward signals.TokenA small unit of text (a word, subword, or punctuation mark) that a language model breaks input into for processing.

Capabilities

Capabilities

Use Case Fit

Glossary