cgato/Thespis-Krangled-7b-v2
cgato/Thespis-Krangled-7b-v2 is a 7 billion parameter language model developed by cgato, fine-tuned on a diverse array of datasets including Dolphin, Ultrachat, and Magiccoder-Evol-Instruct-110k. This model is designed for general conversational AI and instruction-following tasks, leveraging its broad training data to handle varied prompts. With an 8192-token context length, it offers robust performance for interactive applications.
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Overview
cgato/Thespis-Krangled-7b-v2 is a 7 billion parameter language model, distinguished by its extensive fine-tuning on a wide variety of datasets. These include general conversational datasets like Dolphin, Ultrachat, and Capybara, as well as specialized datasets such as Magiccoder-Evol-Instruct-110k for code-related instructions, and ToxicQA for handling nuanced content. The model supports a context length of 8192 tokens, making it suitable for maintaining longer conversations and processing more extensive inputs.
Key Capabilities
- Broad Instruction Following: Trained on diverse datasets like OpenOrca and Airoboros 3.1, enabling it to respond to a wide range of prompts and instructions.
- Conversational AI: Optimized for interactive chat applications, with a recommended prompt format for
Username: {Input}andBotName: {Response}. - Code-Related Tasks: Inclusion of Magiccoder-Evol-Instruct-110k in its training suggests capabilities in understanding and generating code-related text.
- Robustness: Training on datasets like ToxicQA and Yahoo Answers may contribute to its ability to handle varied and sometimes challenging conversational contexts.
Good For
- General-purpose chatbots and virtual assistants requiring versatile instruction following.
- Interactive storytelling and role-playing applications due to its conversational fine-tuning.
- Developers experimenting with models that have been trained on a highly eclectic mix of public datasets to achieve broad utility.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.