In this post, I'll walk you through the process of running Hugging Face models directly using Ollama. Ollama is an advanced platform designed to easily set up and run open-source large language models (LLMs) locally on your machine. On the other hand, Hugging Face offers a massive collection of powerful models, making it one of the leading platforms for machine learning and AI development. Combining these two platforms allows you to access models that might not be available on Ollama but are listed on Hugging Face.
Why This Integration Matters
Ollama enables users to run large language models locally, providing flexibility and privacy when working with AI models. However, sometimes your preferred model might not be available on Ollama. This is where Hugging Face comes in. Hugging Face is a widely used platform for machine learning and data science, offering an extensive library of models and datasets, along with tools to deploy and train models for live applications. By running Hugging Face models directly through Ollama, you can tap into the best of both platforms, accessing models that suit your specific needs.
Step 1: Install Ollama
To get started, you'll first need to install Ollama on your machine.
1. Go to https://ollama.com.
2. Depending on your operating system, download the appropriate installer.
3. Follow the installation instructions, and once completed, you should see an Ollama icon indicating that the installation was successful.
Step 2: Setting Up Ollama
Once Ollama is installed, you can verify the installation by checking the version. Open your terminal and type:
ollama --version
This command should return the installed version of Ollama. For example, if you see something like `0.313`, you know it's set up correctly.
Step 3: Exploring Available Models in Ollama
Ollama offers a range of models that you can explore and run locally. To check the available models, run:
ollama list
This command will display the models currently installed or available for use on Ollama. If your preferred model is not listed, you can turn to Hugging Face.
Step 4: Running Hugging Face Models via Ollama
Now, let's head over to Hugging Face to find and run models that are not available on Ollama. For this example, we’ll use a Hugging Face medical model named `MedV1`.
1. Go to (https://huggingface.co) and search for the model you want.
2. Once you've selected the model, copy its path. For instance, the model path could look something like `username/modelname`.
3. Now, in your terminal, use the following command to run the Hugging Face model via Ollama:
ollama run hf.co/username/modelname
Example ollama run hf.co/mradermacher/llama3.2_1b-medical-v1-GGUF
Ollama will then pull the model from Hugging Face and run it locally.
Step 5: Testing the Model
Let’s say you are running a medical model. You can test it by asking domain-specific questions. For example:
What is mental health?
After entering the query, the model will process it and return a response related to the medical field, specifically focused on mental health. The time taken to load and run the model will depend on its size and complexity, so ensure you have enough storage space and system resources.
By combining the flexibility of Ollama with the vast resources of Hugging Face, you can unlock new possibilities for deploying and running AI models tailored to your specific needs. Whether you're building AI-powered applications or exploring new models, this integration provides a seamless workflow for developers and data scientists alike.