docs: comprehensive README merging original + new content with full credits

README.md

@@ -1,80 +1,85 @@
 ---
 license: mit
+task_categories:
+- text-generation
+language:
+- en
 tags:
+- code
+- llama-cpp
 - llama-cpp-python
 - wheels
 - pre-built
 - binary
+- linux
+- windows
+- macos
 pretty_name: llama-cpp-python Pre-Built Wheels
 size_categories:
 - 1K<n<10K
 ---
 
-# 🏭 llama-cpp-python Pre-Built Wheels
+# 🏭 llama-cpp-python Mega-Factory Wheels
+
+> **"Stop waiting for `pip` to compile. Just install and run."**
 
 The most complete collection of pre-built `llama-cpp-python` wheels in existence — **8,333 wheels** across every platform, Python version, backend, and CPU optimization level.
 
-No more building from source. Just find your wheel and `pip install` it directly.
+No more `cmake`, `gcc`, or compilation hell. No more waiting 10 minutes for a build that might fail. Just find your wheel and `pip install` it directly.
+
+---
+
+## 🚀 Why These Wheels?
+
+Standard wheels target the "lowest common denominator" to avoid crashes on old hardware. This collection goes further — the manylinux wheels are built using a massive **Everything Preset** targeting specific CPU instruction sets, maximizing your **Tokens per Second (T/s)**.
+
+- **Zero Dependencies:** No `cmake`, `gcc`, or `nvcc` required on your target machine.
+- **Every Platform:** Linux (manylinux, aarch64, i686, RISC-V), Windows (amd64, 32-bit), macOS (Intel + Apple Silicon).
+- **Server-Grade Power:** Optimized builds for `Sapphire Rapids`, `Ice Lake`, `Alder Lake`, `Haswell`, and more.
+- **Full Backend Support:** `OpenBLAS`, `MKL`, `Vulkan`, `CLBlast`, `OpenCL`, `RPC`, and plain CPU builds.
+- **Cutting Edge:** Python `3.8` through experimental `3.14`, plus PyPy `pp38`–`pp310`.
+- **GPU Too:** CUDA wheels (cu121–cu124) and macOS Metal wheels included.
+
+---
 
 ## 📊 Collection Stats
 
 | Platform | Wheels |
-|---|---|
+|:---|---:|
 | 🐧 Linux x86_64 (manylinux) | 4,940 |
-| 🍎 macOS Intel (x86_64) | 1,040 |
+| 🍎 macOS Intel (x86\_64) | 1,040 |
 | 🪟 Windows (amd64) | 1,010 |
 | 🪟 Windows (32-bit) | 634 |
 | 🍎 macOS Apple Silicon (arm64) | 289 |
 | 🐧 Linux i686 | 214 |
 | 🐧 Linux aarch64 | 120 |
-| 🐧 Linux x86_64 (plain) | 81 |
+| 🐧 Linux x86\_64 (plain) | 81 |
 | 🐧 Linux RISC-V | 5 |
 | **Total** | **8,333** |
 
+The manylinux builds alone cover **3,600+ combinations** across versions, backends, Python versions, and CPU profiles.
+
+---
+
 ## 🚀 How to Install
 
-Find your wheel using the naming convention below, then install directly:
+### Quick Install
+
+Find your wheel filename (see naming convention below), then:
 
 ```bash
 pip install "https://huggingface.co/datasets/AIencoder/llama-cpp-wheels/resolve/main/YOUR_WHEEL_NAME.whl"
 ```
 
-### Wheel Naming Convention
-
-```
-llama_cpp_python-{version}+{backend}_{profile}-{pytag}-{pytag}-{platform}.whl
-```
-
-**Versions:** `0.2.82` through `0.3.18+`
-
-**Backends (manylinux wheels):**
-- `openblas` — OpenBLAS BLAS acceleration
-- `mkl` — Intel MKL acceleration  
-- `basic` — No BLAS, maximum compatibility
-- `vulkan` — Vulkan GPU
-- `clblast` — CLBlast OpenCL GPU
-- `opencl` — OpenCL GPU
-- `rpc` — Distributed inference
-
-**CPU Profiles (manylinux wheels):**
-- `basic` — Any x86-64 CPU
-- `sse42` — Nehalem+ (2008+)
-- `sandybridge` — AVX (2011+)
-- `ivybridge` — AVX + F16C (2012+)
-- `haswell` — AVX2 + FMA + BMI2 (2013+) ← most common
-- `skylakex` — AVX-512 (2017+)
-- `icelake` — AVX-512 VNNI+VBMI (2019+)
-- `alderlake` — AVX-VNNI (2021+)
-- `sapphirerapids` — AVX-512 BF16 + AMX (2023+)
-
-**Python tags:** `cp38`, `cp39`, `cp310`, `cp311`, `cp312`, `cp313`, `cp314`, `pp38`, `pp39`, `pp310`
-
-### Examples
+### Common Examples
 
 ```bash
-# Linux x86_64, Python 3.11, OpenBLAS, Haswell CPU (most common setup)
+# Linux x86_64, Python 3.11, OpenBLAS, Haswell CPU (most common Linux setup)
 pip install "https://huggingface.co/datasets/AIencoder/llama-cpp-wheels/resolve/main/llama_cpp_python-0.3.18+openblas_haswell-cp311-cp311-manylinux_2_31_x86_64.whl"
 
+# Linux x86_64, Python 3.12, Basic CPU (maximum compatibility)
+pip install "https://huggingface.co/datasets/AIencoder/llama-cpp-wheels/resolve/main/llama_cpp_python-0.3.18+basic_basic-cp312-cp312-manylinux_2_31_x86_64.whl"
+
 # Windows, Python 3.11
 pip install "https://huggingface.co/datasets/AIencoder/llama-cpp-wheels/resolve/main/llama_cpp_python-0.3.18-cp311-cp311-win_amd64.whl"
 
@@ -83,17 +88,101 @@ pip install "https://huggingface.co/datasets/AIencoder/llama-cpp-wheels/resolve/
 
 # macOS Intel, Python 3.11
 pip install "https://huggingface.co/datasets/AIencoder/llama-cpp-wheels/resolve/main/llama_cpp_python-0.3.18-cp311-cp311-macosx_10_9_x86_64.whl"
+
+# Linux ARM64 (Raspberry Pi, AWS Graviton), Python 3.11
+pip install "https://huggingface.co/datasets/AIencoder/llama-cpp-wheels/resolve/main/llama_cpp_python-0.3.18-cp311-cp311-linux_aarch64.whl"
 ```
 
-## 🏗️ Sources
+---
+
+## 📁 Wheel Naming Convention
+
+### manylinux wheels (custom-built)
 
-- **manylinux wheels** — Built by the [Ultimate Llama Wheel Factory](https://huggingface.co/AIencoder) — a distributed 4-worker HuggingFace Space system covering every llama.cpp cmake option possible on manylinux
-- **Windows / macOS / Linux ARM wheels** — Sourced from [abetlen/llama-cpp-python](https://github.com/abetlen/llama-cpp-python) official releases
+```
+llama_cpp_python-{version}+{backend}_{profile}-{pytag}-{pytag}-{platform}.whl
+```
+
+**Versions covered:** `0.3.0` through `0.3.18+`
+
+**Backends:**
+
+| Backend | Description |
+|:---|:---|
+| `openblas` | OpenBLAS BLAS acceleration — best general-purpose CPU performance |
+| `mkl` | Intel MKL acceleration — best on Intel CPUs |
+| `basic` | No BLAS, maximum compatibility |
+| `vulkan` | Vulkan GPU backend |
+| `clblast` | CLBlast OpenCL GPU backend |
+| `opencl` | Generic OpenCL GPU backend |
+| `rpc` | Distributed inference over network |
+
+**CPU Profiles:**
+
+| Profile | Instruction Sets | Era | Notes |
+|:---|:---|:---|:---|
+| `basic` | x86-64 baseline | Any | Maximum compatibility |
+| `sse42` | SSE 4.2 | 2008+ | Nehalem |
+| `sandybridge` | AVX | 2011+ | |
+| `ivybridge` | AVX + F16C | 2012+ | |
+| `haswell` | AVX2 + FMA + BMI2 | 2013+ | **Most common** |
+| `skylakex` | AVX-512 | 2017+ | |
+| `icelake` | AVX-512 + VNNI + VBMI | 2019+ | |
+| `alderlake` | AVX-VNNI | 2021+ | |
+| `sapphirerapids` | AVX-512 BF16 + AMX | 2023+ | Highest performance |
+
+**Python tags:** `cp38`, `cp39`, `cp310`, `cp311`, `cp312`, `cp313`, `cp314`, `pp38`, `pp39`, `pp310`
+
+**Platform:** `manylinux_2_31_x86_64` (glibc 2.31+, compatible with Ubuntu 20.04+, Debian 11+)
+
+### Windows / macOS / Linux ARM wheels (from abetlen)
+
+```
+llama_cpp_python-{version}-{pytag}-{pytag}-{platform}.whl
+```
+
+These are the official pre-built wheels from the upstream maintainer, covering versions `0.2.82` through `0.3.18+`.
+
+---
+
+## 🔍 How to Find Your Wheel
+
+1. **Identify your Python version:** `python --version` → e.g. `3.11` → tag `cp311`
+2. **Identify your platform:**
+   - Linux x86\_64 → `manylinux_2_31_x86_64`
+   - Windows 64-bit → `win_amd64`
+   - macOS Apple Silicon → `macosx_11_0_arm64`
+   - macOS Intel → `macosx_10_9_x86_64`
+3. **Pick a backend** (manylinux only): `openblas` for most use cases
+4. **Pick a CPU profile** (manylinux only): `haswell` works on virtually all modern CPUs
+5. **Browse the files** in this repo or construct the filename directly
+
+---
+
+## 🏗️ Sources & Credits
+
+### manylinux Wheels — Built by AIencoder
+The 4,940 manylinux x86\_64 wheels were built by a distributed **4-worker HuggingFace Space factory** system (`AIencoder/wheel-factory-*`) — a custom-built automated pipeline covering every possible llama.cpp cmake option on manylinux:
+- Every backend: OpenBLAS, MKL, Basic, Vulkan, CLBlast, OpenCL, RPC
+- Every CPU hardware profile from baseline x86-64 up to Sapphire Rapids AMX
+- Python 3.8 through 3.14
+- llama-cpp-python versions 0.3.0 through 0.3.18+
+
+### Windows / macOS / Linux ARM Wheels — abetlen
+The remaining 3,393 wheels (Windows, macOS, Linux aarch64/i686/riscv64, PyPy) were sourced from the official releases by **Andrei Betlen ([@abetlen](https://github.com/abetlen))**, the original author and maintainer of `llama-cpp-python`. These include:
+- CPU wheels for all platforms via `https://abetlen.github.io/llama-cpp-python/whl/cpu/`
+- Metal wheels for macOS GPU acceleration
+- CUDA wheels (cu121–cu124) for Windows and Linux
+
+> All credit for the underlying library goes to **Georgi Gerganov ([@ggerganov](https://github.com/ggerganov))** and the [llama.cpp](https://github.com/ggml-org/llama.cpp) team, and to **Andrei Betlen** for the Python bindings.
+
+---
 
 ## 📝 Notes
 
-- All wheels are MIT licensed (same as llama-cpp-python)
-- manylinux wheels target `manylinux_2_31_x86_64` (glibc 2.31+, Ubuntu 20.04+)
-- CUDA wheels for Windows/macOS are included (cu121–cu124)
-- Metal wheels for macOS are included
+- All wheels are **MIT licensed** (same as llama-cpp-python upstream)
+- manylinux wheels require **glibc 2.31+** (Ubuntu 20.04+, Debian 11+)
+- `manylinux` and `linux_x86_64` are **not the same thing** — manylinux wheels have broad distro compatibility, plain linux wheels do not
+- CUDA wheels require the matching CUDA toolkit to be installed
+- Metal wheels require macOS 11.0+ and an Apple Silicon or AMD GPU
 - This collection is updated periodically as new versions are released