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--- |
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license: apache-2.0 |
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language: |
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- en |
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pipeline_tag: text-generation |
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library_name: transformers |
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base_model: DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it |
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tags: |
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- llama-cpp |
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- gguf-my-repo |
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--- |
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# DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it-Q8_0-GGUF |
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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. |
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Refer to the [original model card](https://huggingface.co/DoeyLLM/OneLLM-Doey-V1-Llama-3.2-1B-it) for more details on the model. |
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### **Quick Start for iOS/Android** |
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 |
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Follow these steps to integrate the **DoeyLLM** model using the OneLLM app: |
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1. **Download OneLLM** |
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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. |
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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. |
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3. **Load the DoeyLLM Model** |
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Use the OneLLM interface to load the DoeyLLM model directly into the app: |
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- Navigate to the **Model Library**. |
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- Search for `DoeyLLM`. |
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- Select the model and tap **Download** to store it locally on your device. |
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4. **Start Conversing** |
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Once the model is loaded, you can begin interacting with it through the app's chat interface. For example: |
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- Tap the **Chat** tab. |
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- Type your question or prompt, such as: |
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> "Explain the significance of AI in education." |
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- Receive real-time, intelligent responses generated locally. |
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### **Key Features of OneLLM** |
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- **Versatile Models**: Supports various LLMs, including Llama, Gemma, and Qwen. |
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- **Private & Secure**: All processing occurs locally on your device, ensuring data privacy. |
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- **Offline Capability**: Use the app without requiring an internet connection. |
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- **Fast Performance**: Optimized for mobile devices, delivering low-latency responses. |
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For more details or support, visit the [OneLLM App Store page](https://apps.apple.com/us/app/onellm-private-ai-gpt-llm/id6737907910). |
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## Use with llama.cpp |
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Install llama.cpp through brew (works on Mac and Linux) |
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```bash |
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brew install llama.cpp |
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``` |
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Invoke the llama.cpp server or the CLI. |
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### CLI: |
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```bash |
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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" |
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``` |
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### Server: |
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```bash |
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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 |
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``` |
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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. |
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Step 1: Clone llama.cpp from GitHub. |
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``` |
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git clone https://github.com/ggerganov/llama.cpp |
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``` |
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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). |
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``` |
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cd llama.cpp && LLAMA_CURL=1 make |
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``` |
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Step 3: Run inference through the main binary. |
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``` |
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./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" |
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``` |
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or |
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``` |
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./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 |
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``` |
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