prithivMLmods
/

Novaeus-Promptist-7B-Instruct

@@ -1,96 +1,108 @@
----
-license: creativeml-openrail-m
-datasets:
-- prithivMLmods/Prompt-Enhancement-Mini
-- gokaygokay/prompt-enhancement-75k
-- gokaygokay/prompt-enhancer-dataset
-language:
-- en
-base_model:
-- Qwen/Qwen2.5-7B-Instruct
-pipeline_tag: text-generation
-library_name: transformers
-tags:
-- Qwen2.5
-- Prompt_Enhance
-- 7B
-- Instruct
-- safetensors
-- pytorch
-- Promptist-Instruct
-- text-generation-inference
-- art
----
-### 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** |
-|--------------------------------------------|---------------|------------------------------------------|-------------------|
-| `.gitattributes`                           | 1.57 kB       | Git attributes configuration for LFS.    | Uploaded          |
-| `README.md`                                | 400 Bytes     | Documentation about the model.           | Updated           |
-| `added_tokens.json`                        | 657 Bytes     | Custom tokens for tokenizer.             | Uploaded          |
-| `config.json`                              | 860 Bytes     | Configuration for the model.             | Uploaded          |
-| `generation_config.json`                   | 281 Bytes     | Configuration for text generation.       | Uploaded          |
-| `merges.txt`                               | 1.82 MB       | Byte-pair encoding (BPE) merge rules.    | Uploaded          |
-| `pytorch_model-00001-of-00004.bin`         | 4.88 GB       | Model weights (split part 1).            | Uploaded (LFS)    |
-| `pytorch_model-00002-of-00004.bin`         | 4.93 GB       | Model weights (split part 2).            | Uploaded (LFS)    |
-| `pytorch_model-00003-of-00004.bin`         | 4.33 GB       | Model weights (split part 3).            | Uploaded (LFS)    |
-| `pytorch_model-00004-of-00004.bin`         | 1.09 GB       | Model weights (split part 4).            | Uploaded (LFS)    |
-| `pytorch_model.bin.index.json`             | 28.1 kB       | Index file for model weights.            | Uploaded          |
-| `special_tokens_map.json`                  | 644 Bytes     | Map of special tokens for tokenizer.     | Uploaded          |
-| `tokenizer.json`                           | 11.4 MB       | Tokenizer data in JSON format.           | Uploaded (LFS)    |
-| `tokenizer_config.json`                    | 7.73 kB       | Tokenizer configuration file.            | Uploaded          |
-| `vocab.json`                               | 2.78 MB       | Vocabulary for tokenizer.                | Uploaded          |
----
-![Screenshot 2024-12-07 113150.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/pqFaT-78hssi106bfJwpN.png)
-### **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.
 ---

+---
+license: creativeml-openrail-m
+datasets:
+- prithivMLmods/Prompt-Enhancement-Mini
+- gokaygokay/prompt-enhancement-75k
+- gokaygokay/prompt-enhancer-dataset
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-7B-Instruct
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- Qwen2.5
+- Prompt_Enhance
+- 7B
+- Instruct
+- safetensors
+- pytorch
+- Promptist-Instruct
+- text-generation-inference
+- art
+---
+### 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** |
+|--------------------------------------------|---------------|------------------------------------------|-------------------|
+| `.gitattributes`                           | 1.57 kB       | Git attributes configuration for LFS.    | Uploaded          |
+| `README.md`                                | 400 Bytes     | Documentation about the model.           | Updated           |
+| `added_tokens.json`                        | 657 Bytes     | Custom tokens for tokenizer.             | Uploaded          |
+| `config.json`                              | 860 Bytes     | Configuration for the model.             | Uploaded          |
+| `generation_config.json`                   | 281 Bytes     | Configuration for text generation.       | Uploaded          |
+| `merges.txt`                               | 1.82 MB       | Byte-pair encoding (BPE) merge rules.    | Uploaded          |
+| `pytorch_model-00001-of-00004.bin`         | 4.88 GB       | Model weights (split part 1).            | Uploaded (LFS)    |
+| `pytorch_model-00002-of-00004.bin`         | 4.93 GB       | Model weights (split part 2).            | Uploaded (LFS)    |
+| `pytorch_model-00003-of-00004.bin`         | 4.33 GB       | Model weights (split part 3).            | Uploaded (LFS)    |
+| `pytorch_model-00004-of-00004.bin`         | 1.09 GB       | Model weights (split part 4).            | Uploaded (LFS)    |
+| `pytorch_model.bin.index.json`             | 28.1 kB       | Index file for model weights.            | Uploaded          |
+| `special_tokens_map.json`                  | 644 Bytes     | Map of special tokens for tokenizer.     | Uploaded          |
+| `tokenizer.json`                           | 11.4 MB       | Tokenizer data in JSON format.           | Uploaded (LFS)    |
+| `tokenizer_config.json`                    | 7.73 kB       | Tokenizer configuration file.            | Uploaded          |
+| `vocab.json`                               | 2.78 MB       | Vocabulary for tokenizer.                | Uploaded          |
+---
+![Screenshot 2024-12-07 113150.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/pqFaT-78hssi106bfJwpN.png)
+### **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.
 ---