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X-Ray_Alpha-GGUF

GGUF
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llama-cpp
matrixportal
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@@ -7,49 +7,75 @@ language:
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  license: gemma
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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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  # oncu/X-Ray_Alpha-GGUF
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- This model was converted to GGUF format from [`SicariusSicariiStuff/X-Ray_Alpha`](https://huggingface.co/SicariusSicariiStuff/X-Ray_Alpha) 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/SicariusSicariiStuff/X-Ray_Alpha) for more details on the model.
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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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-
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- ```bash
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- brew install llama.cpp
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-
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- ```
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- Invoke the llama.cpp server or the CLI.
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-
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- ### CLI:
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- ```bash
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- llama-cli --hf-repo oncu/X-Ray_Alpha-GGUF --hf-file x-ray_alpha-q5_0.gguf -p "The meaning to life and the universe is"
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- ```
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-
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- ### Server:
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- ```bash
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- llama-server --hf-repo oncu/X-Ray_Alpha-GGUF --hf-file x-ray_alpha-q5_0.gguf -c 2048
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- ```
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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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-
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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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-
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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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-
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- Step 3: Run inference through the main binary.
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- ```
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- ./llama-cli --hf-repo oncu/X-Ray_Alpha-GGUF --hf-file x-ray_alpha-q5_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 oncu/X-Ray_Alpha-GGUF --hf-file x-ray_alpha-q5_0.gguf -c 2048
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: gemma
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  tags:
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  - llama-cpp
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+ - matrixportal
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  ---
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  # oncu/X-Ray_Alpha-GGUF
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+ This model was converted to GGUF format from [`SicariusSicariiStuff/X-Ray_Alpha`](https://huggingface.co/SicariusSicariiStuff/X-Ray_Alpha) using llama.cpp via the ggml.ai's [all-gguf-same-where](https://huggingface.co/spaces/matrixportal/all-gguf-same-where) space.
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  Refer to the [original model card](https://huggingface.co/SicariusSicariiStuff/X-Ray_Alpha) for more details on the model.
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+ ## ✅ Quantized Models Download List
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+
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+ ### 🔍 Recommended Quantizations
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+ - **✨ General CPU Use:** [`Q4_K_M`](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q4_k_m.gguf) (Best balance of speed/quality)
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+ - **📱 ARM Devices:** [`Q4_0`](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q4_0.gguf) (Optimized for ARM CPUs)
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+ - **🏆 Maximum Quality:** [`Q8_0`](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q8_0.gguf) (Near-original quality)
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+
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+ ### 📦 Full Quantization Options
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+ | 🚀 Download | 🔢 Type | 📝 Notes |
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+ |:---------|:-----|:------|
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q2_k.gguf) | ![Q2_K](https://img.shields.io/badge/Q2_K-1A73E8) | Basic quantization |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q3_k_s.gguf) | ![Q3_K_S](https://img.shields.io/badge/Q3_K_S-34A853) | Small size |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q3_k_m.gguf) | ![Q3_K_M](https://img.shields.io/badge/Q3_K_M-FBBC05) | Balanced quality |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q3_k_l.gguf) | ![Q3_K_L](https://img.shields.io/badge/Q3_K_L-4285F4) | Better quality |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q4_0.gguf) | ![Q4_0](https://img.shields.io/badge/Q4_0-EA4335) | Fast on ARM |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q4_k_s.gguf) | ![Q4_K_S](https://img.shields.io/badge/Q4_K_S-673AB7) | Fast, recommended |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q4_k_m.gguf) | ![Q4_K_M](https://img.shields.io/badge/Q4_K_M-673AB7) ⭐ | Best balance |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q5_0.gguf) | ![Q5_0](https://img.shields.io/badge/Q5_0-FF6D01) | Good quality |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q5_k_s.gguf) | ![Q5_K_S](https://img.shields.io/badge/Q5_K_S-0F9D58) | Balanced |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q5_k_m.gguf) | ![Q5_K_M](https://img.shields.io/badge/Q5_K_M-0F9D58) | High quality |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q6_k.gguf) | ![Q6_K](https://img.shields.io/badge/Q6_K-4285F4) 🏆 | Very good quality |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-q8_0.gguf) | ![Q8_0](https://img.shields.io/badge/Q8_0-EA4335) ⚡ | Fast, best quality |
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+ | [Download](https://huggingface.co/oncu/X-Ray_Alpha-GGUF/resolve/main/x-ray_alpha-f16.gguf) | ![F16](https://img.shields.io/badge/F16-000000) | Maximum accuracy |
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+
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+ 💡 **Tip:** Use `F16` for maximum precision when quality is critical
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+
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+
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+ ---
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+ # 🚀 Applications and Tools for Locally Quantized LLMs
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+ ## 🖥️ Desktop Applications
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+
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+ | Application | Description | Download Link |
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+ |-----------------|----------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
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+ | **Llama.cpp** | A fast and efficient inference engine for GGUF models. | [GitHub Repository](https://github.com/ggml-org/llama.cpp) |
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+ | **Ollama** | A streamlined solution for running LLMs locally. | [Website](https://ollama.com/) |
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+ | **AnythingLLM** | An AI-powered knowledge management tool. | [GitHub Repository](https://github.com/Mintplex-Labs/anything-llm) |
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+ | **Open WebUI** | A user-friendly web interface for running local LLMs. | [GitHub Repository](https://github.com/open-webui/open-webui) |
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+ | **GPT4All** | A user-friendly desktop application supporting various LLMs, compatible with GGUF models. | [GitHub Repository](https://github.com/nomic-ai/gpt4all) |
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+ | **LM Studio** | A desktop application designed to run and manage local LLMs, supporting GGUF format. | [Website](https://lmstudio.ai/) |
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+ | **GPT4All Chat**| A chat application compatible with GGUF models for local, offline interactions. | [GitHub Repository](https://github.com/nomic-ai/gpt4all) |
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+
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+ ---
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+
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+ ## 📱 Mobile Applications
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+
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+ | Application | Description | Download Link |
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+ |-------------------|----------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
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+ | **ChatterUI** | A simple and lightweight LLM app for mobile devices. | [GitHub Repository](https://github.com/Vali-98/ChatterUI) |
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+ | **Maid** | Mobile Artificial Intelligence Distribution for running AI models on mobile devices. | [GitHub Repository](https://github.com/Mobile-Artificial-Intelligence/maid) |
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+ | **PocketPal AI** | A mobile AI assistant powered by local models. | [GitHub Repository](https://github.com/a-ghorbani/pocketpal-ai) |
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+ | **Layla** | A flexible platform for running various AI models on mobile devices. | [Website](https://www.layla-network.ai/) |
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+
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+ ---
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+
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+ ## 🎨 Image Generation Applications
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+
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+ | Application | Description | Download Link |
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+ |-------------------------------------|----------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
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+ | **Stable Diffusion** | An open-source AI model for generating images from text. | [GitHub Repository](https://github.com/CompVis/stable-diffusion) |
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+ | **Stable Diffusion WebUI** | A web application providing access to Stable Diffusion models via a browser interface. | [GitHub Repository](https://github.com/AUTOMATIC1111/stable-diffusion-webui) |
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+ | **Local Dream** | Android Stable Diffusion with Snapdragon NPU acceleration. Also supports CPU inference. | [GitHub Repository](https://github.com/xororz/local-dream) |
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+ | **Stable-Diffusion-Android (SDAI)** | An open-source AI art application for Android devices, enabling digital art creation. | [GitHub Repository](https://github.com/ShiftHackZ/Stable-Diffusion-Android) |
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+
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+ ---
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+