argilla/CapybaraHermes-2.5-Mistral-7B
CapybaraHermes-2.5-Mistral-7B is a 7 billion parameter language model developed by Argilla, preference-tuned from OpenHermes-2.5-Mistral-7B. It is optimized for multi-turn conversational performance, demonstrating improved MTBench Second Turn scores compared to its base model and Mistral-7B-Instruct-v0.2. This model is suitable for chat applications requiring consistent performance across extended dialogues.
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Model Overview
CapybaraHermes-2.5-Mistral-7B is a 7 billion parameter chat model developed by Argilla, built upon the OpenHermes-2.5-Mistral-7B architecture. It has been preference-tuned using LoRA and TRL for 3 epochs on Argilla's dpo mix 7k dataset, and is the launching partner for the capybara-dpo dataset.
Key Capabilities & Performance
This model's primary differentiation lies in its enhanced multi-turn conversational performance. Benchmarking against OpenHermes-2.5-Mistral-7B and Mistral-7B-Instruct-v0.2, CapybaraHermes-2.5-Mistral-7B shows notable improvements in the MTBench Second Turn scores, achieving 7.5625 compared to 7.2875 and 7.1 respectively. It also demonstrates strong overall performance across various benchmarks:
- AGIEval: 43.8
- GPT4All: 73.35
- Bigbench: 42.44
- MTBench Average: 7.903125
Use Cases
This model is particularly well-suited for applications requiring robust and consistent performance in multi-turn dialogues, such as chatbots, conversational AI agents, and interactive assistants where maintaining context and coherence over several exchanges is crucial.