---
license: apache-2.0
language:
- en
pipeline_tag: text-generation
library_name: transformers
base_model: DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it
tags:
- llama-cpp
- gguf-my-repo
---

# DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it-Q8_0-GGUF
This model was converted to GGUF format from [`DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it`](https://huggingface.co/DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it) for more details on the model.

### **Quick Start for iOS/Android**

Follow these steps to integrate the **DoeyLLM** model using the OneLLM app:

1. **Download OneLLM**  
   iOS: Get the app from the [App Store](https://apps.apple.com/us/app/llm-all-in-one-onellm-pro/id6740195165) and install it on your iOS device.

   Android: Get the app from the [Play Store](https://play.google.com/store/apps/details?id=com.esotech.onellmpro&hl=en_US) and install it on your Android device.

3. **Load the DoeyLLM Model**  
   Use the OneLLM interface to load the DoeyLLM model directly into the app:
   - Navigate to the **Model Library**.
   - Search for `DoeyLLM`.
   - Select the model and tap **Download** to store it locally on your device.
4. **Start Conversing**  
   Once the model is loaded, you can begin interacting with it through the app's chat interface. For example:
   - Tap the **Chat** tab.
   - Type your question or prompt, such as:
     > "Explain the significance of AI in education."
   - Receive real-time, intelligent responses generated locally.

### **Key Features of OneLLM**
- **Versatile Models**: Supports various LLMs, including Llama, Gemma, and Qwen.
- **Private & Secure**: All processing occurs locally on your device, ensuring data privacy.
- **Offline Capability**: Use the app without requiring an internet connection.
- **Fast Performance**: Optimized for mobile devices, delivering low-latency responses.

For more details or support, visit the [OneLLM App Store page](https://apps.apple.com/us/app/onellm-private-ai-gpt-llm/id6737907910).

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it-Q8_0-GGUF --hf-file onellm-doey-v1-llama-3.2-1b-it-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it-Q8_0-GGUF --hf-file onellm-doey-v1-llama-3.2-1b-it-q8_0.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it-Q8_0-GGUF --hf-file onellm-doey-v1-llama-3.2-1b-it-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it-Q8_0-GGUF --hf-file onellm-doey-v1-llama-3.2-1b-it-q8_0.gguf -c 2048
```