Initial upload of TorchScript model weights and documentation

LICENSE

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+WEIGHTS LICENSE WARNING: While the original code is MIT, these pre-trained weights are derived from research-only datasets. They are distributed under CC-BY-NC 4.0.
+
+---
+
+MIT License
+
+Copyright (c) Meta Platforms, Inc. and affiliates.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+---
+license: cc-by-nc-4.0
+tags:
+- audio-separation
+- demucs
+- libtorch
+- coreml
+- metal
+- ios
+- macos
+pipeline_tag: audio-source-separation
+---
+
+# HTDemucs (LibTorch / CoreML Ready)
+
+This repository contains **TorchScript (`.pt`)** exports of the [Hybrid Transformer Demucs (htdemucs)](https://github.com/facebookresearch/demucs) model by Meta Research. 
+
+These models are optimized for **C++ Inference** (using LibTorch) on Apple Silicon (Metal/MPS) and CPU.
+
+## ⚠️ License & Attribution
+
+*   **Original Model Code:** MIT License (Copyright Meta Platforms, Inc.)
+*   **Pre-Trained Weights:** [CC-BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) (Research constraints derived from training data).
+
+**Attribution:** 
+> Original work by **Meta Research**. Based on the paper "Hybrid Transformers for Music Source Separation" by Alexandre Défossez et al.
+> Source Repository: [facebookresearch/demucs](https://github.com/facebookresearch/demucs)
+
+**Disclaimer:** 
+> This is a **format conversion only**. No fine-tuning was performed. The weights are numerically identical to the original release, but packaged for C++ execution without Python dependencies.
+
+## Model Variants
+
+| Filename | Description | Chunk Size | Target Device |
+| :--- | :--- | :--- | :--- |
+| `htdemucs_ft.pt` | **Fast Trace** (Recommended) | 8.0s | Metal (MPS) / GPU |
+| `htdemucs_6s.pt` | **6-Stem** (Guitar/Piano) | 8.0s | Metal (MPS) / GPU |
+| `htdemucs_cpu.pt` | CPU Fallback | 8.0s | CPU |
+
+## Usage (C++)
+
+These models are designed to be loaded directly in C++ using `torch::jit::load()`:
+
+```cpp
+#include <torch/script.h>
+
+auto module = torch::jit::load("htdemucs_ft.pt");
+module.to(torch::kMPS); // Or kCPU
+module.eval();
+
+// Input: [1, 2, Samples]
+auto output = module.forward({input_tensor}).toTensor();
+```
+
+## Integrity
+
+SHA256 checksums are provided in `SHA256SUMS.txt` to verify file integrity.

SHA256SUMS.txt

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+26422280a8ae71a232b0db52e07cd6e60f6e35bf4094e35711f3b36e6bf0d42b  htdemucs_6s.pt
+534b8bb5700fd7199c519a9fc395fd277418f4d8baaf917924965e0b1afeaeb6  htdemucs_cpu.pt
+2bccb2bccb8310d1369440361f8541eee34a339eb55e436d19e7e0f45978289b  htdemucs_ft.pt

htdemucs_6s.pt

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+size 110534647

htdemucs_cpu.pt

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+oid sha256:534b8bb5700fd7199c519a9fc395fd277418f4d8baaf917924965e0b1afeaeb6
+size 168823853

htdemucs_ft.pt

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+size 168832923