Update README.md

README.md

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 - art
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-### Novaeus-Promptist-7B-Instruct Uploaded Model Files:
+### Novaeus-Promptist-7B-Instruct Uploaded Model Files
+
+The **Novaeus-Promptist-7B-Instruct** is a fine-tuned large language model derived from the **Qwen2.5-7B-Instruct** base model. It is optimized for **prompt enhancement, text generation**, and **instruction-following tasks**, providing high-quality outputs tailored to various applications.
 
 | **File Name [ Uploaded Files ]**                              | **Size**      | **Description**                          | **Upload Status** |
 |--------------------------------------------|---------------|------------------------------------------|-------------------|
@@ -42,4 +44,54 @@ tags:
 | `tokenizer_config.json`                    | 7.73 kB       | Tokenizer configuration file.            | Uploaded          |
 | `vocab.json`                               | 2.78 MB       | Vocabulary for tokenizer.                | Uploaded          |
 
+---
+
+### **Key Features:**
+
+1. **Prompt Refinement:**  
+   Designed to enhance input prompts by rephrasing, clarifying, and optimizing for more precise outcomes.
+
+2. **Instruction Following:**  
+   Accurately follows complex user instructions for various generation tasks, including creative writing, summarization, and question answering.
+
+3. **Customization and Fine-Tuning:**  
+   Incorporates datasets specifically curated for prompt optimization, enabling seamless adaptation to specific user needs.
+
+---
+
+### **Training Details:**
+- **Base Model:** [Qwen2.5-7B-Instruct](#)
+- **Datasets Used for Fine-Tuning:**
+  - **gokaygokay/prompt-enhancer-dataset:** Focuses on prompt engineering with 17.9k samples.
+  - **gokaygokay/prompt-enhancement-75k:** Encompasses a wider array of prompt styles with 73.2k samples.
+  - **prithivMLmods/Prompt-Enhancement-Mini:** A compact dataset (1.16k samples) for iterative refinement.
+
+---
+### **Capabilities:**
+
+- **Prompt Optimization:**  
+   Automatically refines and enhances user-input prompts for better generation results.
+  
+- **Instruction-Based Text Generation:**  
+   Supports diverse tasks, including:
+   - Creative writing (stories, poems, scripts).
+   - Summaries and paraphrasing.
+   - Custom Q&A systems.
+
+- **Efficient Fine-Tuning:**  
+   Adaptable to additional fine-tuning tasks by leveraging the model's existing high-quality instruction-following capabilities.
+
+---
+
+### **Usage Instructions:**
+
+1. **Setup:**  
+   - Ensure all necessary model files, including shards, tokenizer configurations, and index files, are downloaded and placed in the correct directory.
+
+2. **Load Model:**  
+   Use PyTorch or Hugging Face Transformers to load the model and tokenizer. Ensure `pytorch_model.bin.index.json` is correctly set for efficient shard-based loading.
+
+3. **Customize Generation:**  
+   Adjust parameters in `generation_config.json` to control aspects such as temperature, top-p sampling, and maximum sequence length.
+
 ---