The Llama-Doctor-3.2-3B-Instruct model is designed for text generation tasks, particularly in contexts where instruction-following capabilities are needed. This model is a fine-tuned version of the base Llama-3.2-3B-Instruct model and is optimized for understanding and responding to user-provided instructions or prompts. The model has been trained on a specialized dataset, avaliev/chat_doctor, to enhance its performance in providing conversational or advisory responses, especially in medical or technical fields.
File Name [ Model File ]
Size
Description
Upload Status
.gitattributes
1.82 kB
Git attributes file
Uploaded
README.md
242 Bytes
Updated README file
Uploaded
config.json
31 Bytes
Model configuration
Uploaded
Llama-Doctor-3.2-3B-Instruct.F16.gguf
6.43 GB
PyTorch model file (F16)
Uploaded (LFS)
Llama-Doctor-3.2-3B-Instruct.Q4_K_M.gguf
2.02 GB
PyTorch model file (Q4_K_M)
Uploaded (LFS)
Llama-Doctor-3.2-3B-Instruct.Q5_K_M.gguf
2.32 GB
PyTorch model file (Q5_K_M)
Uploaded (LFS)
Llama-Doctor-3.2-3B-Instruct.Q8_0.gguf
3.42 GB
PyTorch model file (Q8_0)
Uploaded (LFS)
Modelfile
2.04 kB
Model file (unknown format)
Uploaded
Key Use Cases:
Conversational AI: Engage in dialogue, answering questions, or providing responses based on user instructions.
Text Generation: Generate content, summaries, explanations, or solutions to problems based on given prompts.
Instruction Following: Understand and execute instructions, potentially in complex or specialized domains like medical, technical, or academic fields.
The model leverages a PyTorch-based architecture and comes with various files such as configuration files, tokenizer files, and special tokens maps to facilitate smooth deployment and interaction.
Intended Applications:
Chatbots for customer support or virtual assistants.
Medical Consultation Tools for generating advice or answering medical queries (given its training on the chat_doctor dataset).
Content Creation tools, helping generate text based on specific instructions.
Problem-solving Assistants that offer explanations or answers to user queries, particularly in instructional contexts.
Run with Ollama [ Ollama Run ]
Overview
Ollama 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.
To get started, download Ollama from https://ollama.com/download and install it on your Windows or Mac system.
Steps to Run GGUF Models
1. Create the Model File
First, create a model file and name it appropriately. For example, you can name your model file metallama.
2. Add the Template Command
In your model file, include a FROM line that specifies the base model file you want to use. For instance:
FROM Llama-3.2-1B.F16.gguf
Ensure that the model file is in the same directory as your script.
3. Create and Patch the Model
Open your terminal and run the following command to create and patch your model:
ollama create metallama -f ./metallama
Once the process is successful, you will see a confirmation message.
To verify that the model was created successfully, you can list all models with:
ollama list
Make sure that metallama appears in the list of models.
Running the Model
To run your newly created model, use the following command in your terminal:
ollama run metallama
Sample Usage
In the command prompt, you can execute:
D:\>ollama run metallama
You can interact with the model like this:
plaintext
1>>> write a mini passage about space x
2Space X, the private aerospace company founded by Elon Musk, is revolutionizing the field of space exploration.
3With its ambitious goals to make humanity a multi-planetary species and establish a sustainable human presence in
4the cosmos, Space X has become a leading player in the industry. The company's spacecraft, like the Falcon 9, have
5demonstrated remarkable capabilities, allowing for the transport of crews and cargo into space with unprecedented
6efficiency. As technology continues to advance, the possibility of establishing permanent colonies on Mars becomes
7increasingly feasible, thanks in part to the success of reusable rockets that can launch multiple times without
8sustaining significant damage. The journey towards becoming a multi-planetary species is underway, and Space X
9plays a pivotal role in pushing the boundaries of human exploration and settlement.
Conclusion
With 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.
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.
