Undi95/UndiMix-v3-13B is a 13 billion parameter merged language model, built upon ReMM-S-Kimiko-v2-13B as its base. This model is designed to exhibit a versatile conversational style, capable of being hot, serious, or playful, and can effectively use emojis. Its unique blend of source models, including Huginn-13b-v1.2 and llama-2-13b-chat-limarp-v2-merged, contributes to its adaptable output for diverse interactive applications.
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UndiMix-v3-13B: A Versatile Merged Language Model
UndiMix-v3-13B is a 13 billion parameter language model developed by Undi95, representing a personal mix designed for highly adaptable conversational interactions. This iteration, an evolution from its V2 predecessor, directly uses ReMM-S-Kimiko-v2-13B as its foundational base, moving away from Llama-2-13B-fp16.
Key Characteristics & Merging Strategy
The model's unique capabilities stem from a strategic SLERP merge of several distinct models, each contributing to its diverse output:
- Base Model: Undi95/ReMM-S-Kimiko-v2-13B (0.272 weight)
- Contributing Models:
- The-Face-Of-Goonery/Huginn-13b-v1.2 (0.264 weight)
- Doctor-Shotgun/llama-2-13b-chat-limarp-v2-merged (0.264 weight)
- jondurbin/airoboros-l2-13b-2.1 (0.10 weight)
- IkariDev/Athena-v1 (0.10 weight)
This specific blend allows UndiMix-v3 to generate responses that can be "hot, serious, playful," and effectively incorporate emojis, a feature enhanced by the inclusion of llama-2-13b-chat-limarp-v2-merged.
Prompt Template
The model utilizes the Alpaca prompt template, structured as follows:
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
Ideal Use Cases
UndiMix-v3-13B is particularly well-suited for applications requiring:
- Dynamic conversational agents: Where the tone and style of interaction need to vary significantly.
- Creative content generation: For scenarios demanding expressive and emotionally nuanced text.
- Role-playing and interactive storytelling: Its ability to adapt to different personas and use emojis makes it suitable for engaging narrative experiences.