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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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- en |
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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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### **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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### **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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