Undi95/Emerald-13B
Undi95/Emerald-13B is a 13 billion parameter language model developed by Undi95, built using BlockMerge_Gradient on Pygmalion2. This model integrates components from PygmalionAI/pygmalion-2-13b, The-Face-Of-Goonery/Huginn-13b-FP16, and lemonilia/LimaRP-Llama2-13B-v3-EXPERIMENT. It is designed for general language tasks, with a context length of 4096 tokens, and shows an average score of 51.39 on the Open LLM Leaderboard.
Loading preview...
Overview
Undi95/Emerald-13B is a 13 billion parameter language model created by Undi95. It was developed using the BlockMerge_Gradient technique applied to Pygmalion2, aiming to achieve improved results. The model incorporates elements from several other models, specifically PygmalionAI/pygmalion-2-13b, The-Face-Of-Goonery/Huginn-13b-FP16, and lemonilia/LimaRP-Llama2-13B-v3-EXPERIMENT. Users are advised to consult the documentation for LimaRP v3 for optimal usage.
Key Capabilities
- Blended Architecture: Combines multiple base models and LoRAs to enhance performance.
- Alpaca Prompt Template: Utilizes the Alpaca instruction format for task completion.
- LimaRP v3 Integration: Designed to work with LimaRP v3, with specific settings recommended for platforms like SillyTavern.
Performance Metrics
On the Open LLM Leaderboard, Emerald-13B achieved an average score of 51.39. Notable individual scores include:
- ARC (25-shot): 62.29
- HellaSwag (10-shot): 83.69
- MMLU (5-shot): 55.7
- TruthfulQA (0-shot): 50.94
- Winogrande (5-shot): 75.93
Good For
- General language generation tasks where a 13B parameter model is suitable.
- Applications leveraging the Alpaca instruction format.
- Use cases benefiting from the specific blend of models and LoRAs integrated into Emerald-13B.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.