--- license: apache-2.0 language: - zho - eng - fra - spa - por - deu - ita - rus - jpn - kor - vie - tha - ara base_model: - Qwen/Qwen2.5-7B-Instruct tags: - not-for-all-audiences ---
WoonaAi presents...
CardProjector is a specialized series of language models, fine-tuned to generate character cards for SillyTavern and for creating characters in general. These models are designed to assist creators and roleplayers by automating the process of crafting detailed and well-structured character cards, ensuring compatibility with SillyTavern's format.
The evaluation was conducted on the Character Creation&Editing validation dataset.
Lower = Better
Model Size | Model Name | PPL Score |
---|---|---|
24B | CardProjector-24B-v3 | 4.3368 |
CardProjector-24B-v1 | 5.0515 | |
14B | CardProjector-14B-v3 | 5.5600 |
CardProjector-14B-v2 | 7.4854 | |
7B | CardProjector-7B-v3 | 5.9373 |
CardProjector-7B-v2 | 7.7422 |
Chat Template: ChatML
Balanced output:
Temperature: 0.7-0.8
Top-P: 0.92
Rp.Pen: 1.07
Top-K: 100
The character creation process: Based on my tests, I would recommend the following approach. To create a well-developed and structured character, I suggest first asking the model to generate the character in a standard, natural format (meaning you shouldn't request formats like YAML or JSON right away), allowing it to describe the character in plain, understandable text. Then, if needed, ask for any necessary adjustments. Once you're satisfied with the result, request the final version to be converted into YAML format. Why YAML? It's an ideal format for structuring and summarizing a character from your chat story. This format is human-readable, and its clear structure is very well processed by RP models (from my tests, it’s even better in some ways than XML). You can simply copy the entire YAML output and paste it into the Description field in Silly Tavern. Alternatively, you can ask the model to convert the resulting card into JSON while leaving the YAML description untouched. I have found this method of using CardProjector v3 to be the most effective.
This model learned on cards for Silly Tavern. I think comments are unnecessary here...
Base Model: Qwen2.5-7B-Instruct License: Apache-2.0 Language: English