Upload TinyCLAP CoreML models

Audio encoder: TinyCLAP_AudioEncoder.mlmodel (~17 MB)
Text encoder: TinyCLAP_TextEncoder.mlmodel (~422 MB)
Preprocessing: mel_filter_bank.json

.gitattributes

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+# CoreML models are large binaries — track via Git LFS
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+**/weight.bin filter=lfs diff=lfs merge=lfs -text
+**/model.mlmodel filter=lfs diff=lfs merge=lfs -text

LICENSE

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+   Copyright [2024] [Francesco Paissan]
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README.md

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+---
+tags:
+  - coreml
+  - audio
+  - clap
+  - semantic-search
+  - onnx  # TODO: remove once CoreML-only is verified
+license: apache-2.0
+---
+
+# TinyCLAP CoreML
+
+CoreML-converted tinyCLAP models for on-device semantic audio search on macOS and iOS.
+
+## What's inside
+
+This repository contains the student tinyCLAP encoder pair converted to CoreML:
+
+| File | Size | Purpose |
+|------|------|---------|
+| `TinyCLAP_AudioEncoder.mlmodel` | ~17 MB | PhiNet-based audio encoder. Consumes log-mel spectrograms and emits 1024-dim L2-normalized embeddings. |
+| `TinyCLAP_TextEncoder.mlmodel` | ~422 MB | BERT-base text encoder. Consumes tokenized text and emits 1024-dim L2-normalized embeddings. |
+| `mel_filter_bank.json` | ~170 KB | Pre-computed 64-bin mel filter bank (Slaney, 50–14000 Hz) for audio preprocessing. |
+| `text_embeddings.json` | ~220 KB | Sample text embeddings for sanity-checking the model output. |
+
+## Architecture
+
+```
+Audio file (44.1 kHz mono)
+    ↓
+STFT (n_fft=1024, hop=320, win=1024, Hann)
+    ↓
+Log-mel spectrogram (64 bins, 50–14000 Hz)
+    ↓
+TinyCLAP_AudioEncoder.mlmodel
+    ↓
+1024-dim L2-normalised embedding
+```
+
+```
+Text query
+    ↓
+BERT tokenization (max_length=100)
+    ↓
+TinyCLAP_TextEncoder.mlmodel
+    ↓
+1024-dim L2-normalised embedding
+```
+
+Cosine similarity between the two embeddings yields semantic relevance scores.
+
+## Preprocessing spec (must match exactly)
+
+| Parameter | Value |
+|-----------|-------|
+| Sample rate | 44100 Hz |
+| Channels | Mono |
+| FFT size | 1024 |
+| Hop length | 320 |
+| Window length | 1024 |
+| Window | Hann |
+| Center | true |
+| Pad mode | reflect |
+| Mel bins | 64 |
+| Mel fmin | 50 Hz |
+| Mel fmax | 14000 Hz |
+| Ref | 1.0 |
+| Amin | 1e-10 |
+| Max text length | 100 tokens |
+| Output shape | `[1, 1, 640, 64]` (batch, channel, time, freq) |
+
+## CoreML conversion details
+
+- **Backend**: `neuralnetwork` (`convert_to="neuralnetwork"`)
+- **Compute units**: `CPU_AND_GPU`
+- **Audio encoder input**: flexible time dimension (640 frames nominal)
+- **Text encoder input**: fixed `[1, 100]` for both `input_ids` and `attention_mask`
+
+The `mlprogram` backend was attempted but produced NaN outputs with PhiNet's BatchNorm statistics; `neuralnetwork` gives bit-exact results.
+
+## Original work
+
+This is a CoreML port of the tinyCLAP architecture (student-teacher CLAP distillation with PhiNet audio encoder and BERT text encoder). The conversion was performed using `coremltools` 9.0 and PyTorch 2.12.
+
+## License
+
+This repository contains CoreML-converted artifacts derived from [tinyCLAP](https://github.com/fpaissan/tinyclap), which is licensed under the **Apache License 2.0**. See [LICENSE](LICENSE) for the full text.
+
+The original model weights, training code, and architecture remain the intellectual property of the original authors (Francesco Paissan et al.). This repository only provides the converted CoreML models and does not claim ownership over the original work.

TinyCLAP_AudioEncoder.mlmodel

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7539be8cd9e73424501641c9a705ece9220ff6a78d788f1b7575f648f48ccd67
+size 17725633

TinyCLAP_TextEncoder.mlmodel

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0777ef993118266be505d9e480c4e088bb20f21a4d3febf9fe5f0ab575c16a38
+size 441980611

upload.sh

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+#!/bin/bash
+set -euo pipefail
+
+# =============================================================================
+# TinyCLAP CoreML — HuggingFace Upload Script
+# =============================================================================
+# Usage:
+#   export HF_TOKEN=hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
+#   ./upload.sh [org/username]
+#
+# The optional argument is the HF namespace. Defaults to the current user's
+# namespace if omitted.
+# =============================================================================
+
+REPO_NAME="tinyclap-coreml"
+NAMESPACE="${1:-}"
+
+if [ -z "$NAMESPACE" ]; then
+    echo "Usage: $0 <hf-namespace>"
+    echo "Example: $0 duhamelc"
+    exit 1
+fi
+
+FULL_REPO="$NAMESPACE/$REPO_NAME"
+
+echo "========================================"
+echo "  TinyCLAP CoreML HF Upload"
+echo "  Target: https://huggingface.co/$FULL_REPO"
+echo "========================================"
+echo
+
+# --- Check prerequisites ------------------------------------------------------
+
+if [ -z "${HF_TOKEN:-}" ]; then
+    echo "Error: HF_TOKEN environment variable is not set."
+    echo "Get your token from https://huggingface.co/settings/tokens"
+    exit 1
+fi
+
+if ! command -v git &> /dev/null; then
+    echo "Error: git is not installed."
+    exit 1
+fi
+
+if ! command -v git-lfs &> /dev/null; then
+    echo "Error: git-lfs is not installed. Install it with: brew install git-lfs"
+    exit 1
+fi
+
+if ! command -v huggingface-cli &> /dev/null; then
+    echo "Warning: huggingface-cli not found. Will use raw git + LFS instead."
+    USE_CLI=false
+else
+    USE_CLI=true
+fi
+
+# --- Verify files exist -------------------------------------------------------
+
+FILES=(
+    "TinyCLAP_AudioEncoder.mlmodel"
+    "TinyCLAP_TextEncoder.mlmodel"
+    "mel_filter_bank.json"
+    "text_embeddings.json"
+    "README.md"
+    "LICENSE"
+    ".gitattributes"
+)
+
+for f in "${FILES[@]}"; do
+    if [ ! -f "$f" ]; then
+        echo "Error: Required file '$f' not found in current directory."
+        exit 1
+    fi
+done
+
+# --- Initialize git repo if needed --------------------------------------------
+
+if [ ! -d ".git" ]; then
+    echo "→ Initializing git repository..."
+    git init
+    git lfs install
+fi
+
+# --- Create or use existing remote -------------------------------------------
+
+if ! git remote get-url origin &> /dev/null; then
+    echo "→ Adding remote origin..."
+    git remote add origin "https://huggingface.co/$FULL_REPO"
+else
+    echo "→ Updating remote origin..."
+    git remote set-url origin "https://huggingface.co/$FULL_REPO"
+fi
+
+# --- Stage and commit ---------------------------------------------------------
+
+echo "→ Staging files..."
+git add -A
+
+if git diff --cached --quiet; then
+    echo "Nothing to commit. Repository is up to date."
+else
+    echo "→ Committing..."
+    git commit --author="Velvox Builder <build@localhost>" -m "Upload TinyCLAP CoreML models
+
+Audio encoder: TinyCLAP_AudioEncoder.mlmodel (~17 MB)
+Text encoder:  TinyCLAP_TextEncoder.mlmodel (~422 MB)
+Preprocessing: mel_filter_bank.json"
+fi
+
+# --- Push ---------------------------------------------------------------------
+
+echo "→ Pushing to HuggingFace..."
+
+if [ "$USE_CLI" = true ]; then
+    huggingface-cli upload "$FULL_REPO" . . --repo-type model --token "$HF_TOKEN"
+else
+    # Raw git push with token in URL
+    git push "https://user:$HF_TOKEN@huggingface.co/$FULL_REPO" main --force
+fi
+
+echo
+echo "========================================"
+echo "  Upload complete!"
+echo "  https://huggingface.co/$FULL_REPO"
+echo "========================================"