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---
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license: creativeml-openrail-m
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datasets:
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- prithivMLmods/Prompt-Enhancement-Mini
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- gokaygokay/prompt-enhancement-75k
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- gokaygokay/prompt-enhancer-dataset
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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base_model:
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- Qwen/Qwen2.5-7B-Instruct
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- Qwen2.5
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- Prompt_Enhance
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- 7B
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- Instruct
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- safetensors
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- pytorch
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- Promptist-Instruct
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- text-generation-inference
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- art
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---
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### Novaeus-Promptist-7B-Instruct Uploaded Model Files
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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.
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| **File Name [ Uploaded Files ]** | **Size** | **Description** | **Upload Status** |
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|--------------------------------------------|---------------|------------------------------------------|-------------------|
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| `.gitattributes` | 1.57 kB | Git attributes configuration for LFS. | Uploaded |
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| `README.md` | 400 Bytes | Documentation about the model. | Updated |
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| `added_tokens.json` | 657 Bytes | Custom tokens for tokenizer. | Uploaded |
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| `config.json` | 860 Bytes | Configuration for the model. | Uploaded |
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| `generation_config.json` | 281 Bytes | Configuration for text generation. | Uploaded |
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| `merges.txt` | 1.82 MB | Byte-pair encoding (BPE) merge rules. | Uploaded |
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| `pytorch_model-00001-of-00004.bin` | 4.88 GB | Model weights (split part 1). | Uploaded (LFS) |
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| `pytorch_model-00002-of-00004.bin` | 4.93 GB | Model weights (split part 2). | Uploaded (LFS) |
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| `pytorch_model-00003-of-00004.bin` | 4.33 GB | Model weights (split part 3). | Uploaded (LFS) |
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| `pytorch_model-00004-of-00004.bin` | 1.09 GB | Model weights (split part 4). | Uploaded (LFS) |
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| `pytorch_model.bin.index.json` | 28.1 kB | Index file for model weights. | Uploaded |
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| `special_tokens_map.json` | 644 Bytes | Map of special tokens for tokenizer. | Uploaded |
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| `tokenizer.json` | 11.4 MB | Tokenizer data in JSON format. | Uploaded (LFS) |
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| `tokenizer_config.json` | 7.73 kB | Tokenizer configuration file. | Uploaded |
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| `vocab.json` | 2.78 MB | Vocabulary for tokenizer. | Uploaded |
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---
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### **Key Features:**
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1. **Prompt Refinement:**
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Designed to enhance input prompts by rephrasing, clarifying, and optimizing for more precise outcomes.
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2. **Instruction Following:**
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Accurately follows complex user instructions for various generation tasks, including creative writing, summarization, and question answering.
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3. **Customization and Fine-Tuning:**
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Incorporates datasets specifically curated for prompt optimization, enabling seamless adaptation to specific user needs.
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---
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### **Training Details:**
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- **Base Model:** [Qwen2.5-7B-Instruct](#)
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- **Datasets Used for Fine-Tuning:**
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- **gokaygokay/prompt-enhancer-dataset:** Focuses on prompt engineering with 17.9k samples.
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- **gokaygokay/prompt-enhancement-75k:** Encompasses a wider array of prompt styles with 73.2k samples.
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- **prithivMLmods/Prompt-Enhancement-Mini:** A compact dataset (1.16k samples) for iterative refinement.
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---
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### **Capabilities:**
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- **Prompt Optimization:**
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Automatically refines and enhances user-input prompts for better generation results.
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- **Instruction-Based Text Generation:**
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Supports diverse tasks, including:
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- Creative writing (stories, poems, scripts).
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- Summaries and paraphrasing.
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- Custom Q&A systems.
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- **Efficient Fine-Tuning:**
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Adaptable to additional fine-tuning tasks by leveraging the model's existing high-quality instruction-following capabilities.
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---
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### **Usage Instructions:**
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1. **Setup:**
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- Ensure all necessary model files, including shards, tokenizer configurations, and index files, are downloaded and placed in the correct directory.
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2. **Load Model:**
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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.
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3. **Customize Generation:**
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Adjust parameters in `generation_config.json` to control aspects such as temperature, top-p sampling, and maximum sequence length.
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--- |
