Update README.md

README.md

@@ -5,7 +5,7 @@ license: apache-2.0
 
 ## Overview
 
-CardProjector-24B-v1 is a specialized language model derived from Mistral Small, fine-tuned to generate character cards for **SillyTavern** in the **chara_card_v2** specification. This model is designed to assist creators and roleplayers by automating the process of crafting detailed and well-structured character cards, ensuring compatibility with SillyTavern's format.
+CardProjector-24B-v1 is a specialized language model derived from Mistral-Small-24B-Instruct-2501, fine-tuned to generate character cards for **SillyTavern** in the **chara_card_v2** specification. This model is designed to assist creators and roleplayers by automating the process of crafting detailed and well-structured character cards, ensuring compatibility with SillyTavern's format.
 
 Whether you're creating NPCs for storytelling, roleplaying games, or interactive fiction, CardProjector-24B-v1 streamlines the workflow while maintaining high-quality outputs tailored to your needs.
 
@@ -17,7 +17,6 @@ Whether you're creating NPCs for storytelling, roleplaying games, or interactive
 - **Rich Character Details**: Produces comprehensive profiles including personality traits, appearance descriptions, example dialogues, and scenario setups.
 - **Customizable Inputs**: Allows users to provide prompts, themes, or specific attributes to guide the generation process.
 - **High-Quality Writing**: Leverages Mistral Small’s robust linguistic capabilities to ensure engaging, coherent, and creative writing.
-- **Roleplay-Friendly**: Optimized for use in collaborative storytelling environments like SillyTavern.
 
 ---
 
@@ -32,110 +31,7 @@ Whether you're creating NPCs for storytelling, roleplaying games, or interactive
 
 ## Getting Started
 
-### Prerequisites
 
-- Python 3.8+
-- Libraries: `transformers`, `torch`, `json`
-- Access to the pre-trained weights of CardProjector-24B-v1 (contact the maintainers for access).
 
-### Installation
 
-```bash
-pip install transformers torch
-```
 
-### Usage Example
-
-Here’s how you can generate a character card using CardProjector-24B-v1:
-
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import json
-
-# Load the model and tokenizer
-model_name = "path_to_CardProjector-24B-v1"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
-
-# Define input prompt
-prompt = """
-Create a character card for a wise old wizard who lives in a forest. 
-He is kind but mysterious, often speaking in riddles. His name is Eldrin.
-"""
-
-# Tokenize and generate
-inputs = tokenizer(prompt, return_tensors="pt")
-outputs = model.generate(**inputs, max_length=512)
-
-# Decode and parse output as JSON
-output_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-character_card = json.loads(output_text)
-
-# Save to file
-with open("eldrin_character_card.json", "w") as f:
-    json.dump(character_card, f, indent=4)
-
-print("Character card saved to eldrin_character_card.json")
-```
-
-### Sample Output (`chara_card_v2` Schema)
-
-```json
-{
-  "name": "Eldrin",
-  "description": "A wise old wizard residing deep within an ancient forest. Known for his kindness and cryptic wisdom.",
-  "personality": "Kind-hearted yet enigmatic, Eldrin enjoys testing others' wit through riddles and puzzles.",
-  "scenario": "You find yourself lost in the dense woods when suddenly, a faint glow reveals a small cottage ahead...",
-  "example_dialogue": [
-    {"speaker": "You", "message": "Can you help me find my way out of this forest?"},
-    {"speaker": "Eldrin", "message": "Ah, the path is not always where it seems. Tell me first—what walks on four legs at dawn?"}
-  ],
-  "metadata": {
-    "version": "chara_card_v2",
-    "tags": ["wizard", "forest", "riddle", "kind"]
-  }
-}
-```
-
----
-
-## Fine-Tuning & Customization
-
-If you'd like to further fine-tune CardProjector-24B-v1 for niche genres or specific styles, follow these steps:
-
-1. Prepare a dataset of character cards in the `chara_card_v2` format.
-2. Use Hugging Face’s `Trainer` API to fine-tune the model.
-3. Evaluate the updated model for consistency and creativity.
-
-For more details, refer to the [Hugging Face Documentation](https://huggingface.co/docs/transformers/training).
-
----
-
-## Limitations
-
-- **Input Sensitivity**: The quality of generated cards depends heavily on the clarity and specificity of the input prompt.
-- **Token Limitations**: Very long prompts may exceed the model’s context window, leading to truncated outputs.
-- **Ethical Considerations**: Ensure that generated content aligns with ethical guidelines, avoiding harmful stereotypes or inappropriate material.
-
----
-
-## Contributing
-
-Contributions are welcome! If you have suggestions, bug reports, or feature requests, please open an issue on our GitHub repository.
-
----
-
-## License
-
-CardProjector-24B-v1 is released under the MIT License. See the [LICENSE](LICENSE) file for more information.
-
----
-
-## Acknowledgments
-
-- Built upon the foundational work of Mistral AI and their Mistral Small model.
-- Inspired by the vibrant communities around SillyTavern and interactive storytelling.
-
----
-
-For questions or support, contact us at [[email protected]].