lodrick-the-lafted/Hermes-Instruct-7B-100K
Hermes-Instruct-7B-100K is a 7 billion parameter instruction-tuned language model developed by lodrick-the-lafted, based on Mistral-7B-Instruct-v0.2. It was fine-tuned using 100K rows of the OpenHermes dataset in Alpaca format, enhancing its instruction-following capabilities. This model is optimized for general-purpose conversational AI and instruction-based tasks, demonstrating solid performance across various reasoning and language understanding benchmarks.
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Hermes-Instruct-7B-100K Overview
Hermes-Instruct-7B-100K is a 7 billion parameter instruction-tuned model developed by lodrick-the-lafted. It is built upon the robust Mistral-7B-Instruct-v0.2 architecture and has been further fine-tuned using 100,000 rows from the teknium/openhermes dataset, formatted in the Alpaca style. This training approach aims to enhance its ability to understand and follow instructions effectively.
Key Capabilities and Features
- Instruction Following: Optimized for responding to a wide range of user instructions, leveraging its fine-tuning on the OpenHermes dataset.
- Flexible Prompting: Supports both the default Mistral-Instruct prompt format (
<s>[INST] {sys_prompt} {instruction} [/INST]) and the Alpaca format ({sys_prompt}\n\n### Instruction:\n{instruction}\n\n### Response:\n). The tokenizer defaults to Alpaca. - Performance: Achieves an average score of 64.96 on the Open LLM Leaderboard, with notable scores including 82.84 on HellaSwag (10-Shot) and 60.95 on MMLU (5-Shot). Detailed evaluation results are available on the Open LLM Leaderboard.
Ideal Use Cases
- General Conversational AI: Suitable for chatbots and virtual assistants requiring strong instruction adherence.
- Text Generation: Effective for generating creative and coherent text based on specific prompts.
- Research and Development: A solid base model for further fine-tuning on domain-specific instruction datasets.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.