prithivMLmods/OpenCoder-1.5B-Instruct-GGUF

1---2license: creativeml-openrail-m3language:4- en5- zh6base_model:7- infly/OpenCoder-1.5B-Instruct8pipeline_tag: text-generation9library_name: transformers10tags:11- llama-cpp12- OpenCoder13---14 15## OpenCoder-1.5B-Instruct-GGUF16 17| File Name                                  | Size    | Description                                                               |18|--------------------------------------------|---------|---------------------------------------------------------------------------|19| `.gitattributes`                           | 2.37kB  | Git configuration file for handling file attributes and LFS rules.        |20| `README.md`                                | 189B    | Basic README file with project information.                               |21| `opencoder-1.5b-instruct-q2_k.gguf`        | 1.14GB  | Instruction-tuned quantized 2-bit model, optimized for lightweight usage. |22| `opencoder-1.5b-instruct-q3_k_l.gguf`      | 1.27GB  | Instruction-tuned quantized 3-bit model (large variant).                  |23| `opencoder-1.5b-instruct-q3_k_m.gguf`      | 1.22GB  | Instruction-tuned quantized 3-bit model (medium variant).                 |24| `opencoder-1.5b-instruct-q3_k_s.gguf`      | 1.14GB  | Instruction-tuned quantized 3-bit model (small variant).                  |25| `opencoder-1.5b-instruct-q4_0.gguf`        | 1.18GB  | Instruction-tuned quantized 4-bit model with basic accuracy optimization. |26| `opencoder-1.5b-instruct-q4_k_m.gguf`      | 1.42GB  | Medium variant of the 4-bit quantized instruction-tuned model.            |27| `opencoder-1.5b-instruct-q4_k_s.gguf`      | 1.36GB  | Small variant of the 4-bit quantized instruction-tuned model.             |28| `opencoder-1.5b-instruct-q5_0.gguf`        | 1.39GB  | Instruction-tuned quantized 5-bit model for higher accuracy.              |29| `opencoder-1.5b-instruct-q5_k_m.gguf`      | 1.52GB  | Medium variant of the 5-bit quantized instruction-tuned model.            |30| `opencoder-1.5b-instruct-q5_k_s.gguf`      | 1.48GB  | Small variant of the 5-bit quantized instruction-tuned model.             |31| `opencoder-1.5b-instruct-q6_k.gguf`        | 1.95GB  | Instruction-tuned quantized 6-bit model for better accuracy.              |32| `opencoder-1.5b-instruct-q8_0.gguf`        | 2.03GB  | Instruction-tuned quantized 8-bit model for high accuracy tasks.          |33 34 35# Run with Ollama 🦙36 37## Overview38 39Ollama is a powerful tool that allows you to run machine learning models effortlessly. This guide will help you download, install, and run your own GGUF models in just a few minutes.40 41## Table of Contents42 43- [Download and Install Ollama](#download-and-install-ollama)44- [Steps to Run GGUF Models](#steps-to-run-gguf-models)45  - [1. Create the Model File](#1-create-the-model-file)46  - [2. Add the Template Command](#2-add-the-template-command)47  - [3. Create and Patch the Model](#3-create-and-patch-the-model)48- [Running the Model](#running-the-model)49- [Sample Usage](#sample-usage)50 51## Download and Install Ollama🦙52 53To get started, download Ollama from [https://ollama.com/download](https://ollama.com/download) and install it on your Windows or Mac system.54 55## Steps to Run GGUF Models56 57### 1. Create the Model File58First, create a model file and name it appropriately. For example, you can name your model file `metallama`.59 60### 2. Add the Template Command61In your model file, include a `FROM` line that specifies the base model file you want to use. For instance:62 63```bash64FROM Llama-3.2-1B.F16.gguf65```66 67Ensure that the model file is in the same directory as your script.68 69### 3. Create and Patch the Model70Open your terminal and run the following command to create and patch your model:71 72```bash73ollama create metallama -f ./metallama74```75 76Once the process is successful, you will see a confirmation message.77 78To verify that the model was created successfully, you can list all models with:79 80```bash81ollama list82```83 84Make sure that `metallama` appears in the list of models.85 86---87 88## Running the Model89 90To run your newly created model, use the following command in your terminal:91 92```bash93ollama run metallama94```95 96### Sample Usage97 98In the command prompt, you can execute:99 100```bash101D:\>ollama run metallama102```103 104You can interact with the model like this:105 106```plaintext107>>> write a mini passage about space x108Space X, the private aerospace company founded by Elon Musk, is revolutionizing the field of space exploration.109With its ambitious goals to make humanity a multi-planetary species and establish a sustainable human presence in110the cosmos, Space X has become a leading player in the industry. The company's spacecraft, like the Falcon 9, have111demonstrated remarkable capabilities, allowing for the transport of crews and cargo into space with unprecedented112efficiency. As technology continues to advance, the possibility of establishing permanent colonies on Mars becomes113increasingly feasible, thanks in part to the success of reusable rockets that can launch multiple times without114sustaining significant damage. The journey towards becoming a multi-planetary species is underway, and Space X115plays a pivotal role in pushing the boundaries of human exploration and settlement.116```117 118---119 120## Conclusion121 122With these simple steps, you can easily download, install, and run your own models using Ollama. Whether you're exploring the capabilities of Llama or building your own custom models, Ollama makes it accessible and efficient.123 124 125- This README provides clear instructions and structured information to help users navigate the process of using Ollama effectively. Adjust any sections as needed based on your specific requirements or additional details you may want to include.