Fabio
c36510c21e
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117 lines
2.8 KiB
JSON
117 lines
2.8 KiB
JSON
{
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"schema_version": 1,
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"family": "whistle_asr",
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"display_name": "Whistle ASR",
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"description": "Whistle offline speech recognition with FP32 GGUF weights, a GGML encoder and a host decoder.",
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"category": "asr",
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"status": "experimental",
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"tasks": [
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"asr"
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],
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"modes": [
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"offline"
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],
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"languages": [
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"en",
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"de",
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"fr",
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"es",
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"it",
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"nl",
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"pl"
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],
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"runtime": {
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"tags": [
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"gguf"
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]
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},
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"capabilities": {},
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"options": {
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"request": [
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{
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"name": "language",
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"type": "string",
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"description": "Force one supported language; omit to detect the language.",
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"required": false
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}
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],
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"session": [
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{
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"name": "exec_plan",
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"type": "string",
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"description": "JSON component execution plans. Component decoder accepts impl native/neon (default native), both on CPU independently of the encoder backend. The experimental neon implementation accelerates the vocabulary projection with the framework NEON library and requires ENGINE_ENABLE_NEON=ON and AArch64 NEON. No artifacts or params are used.",
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"required": false,
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"default": "{}"
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}
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],
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"load": []
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},
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"package_defaults": {
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"download": {
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"kind": "huggingface_snapshot",
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"repo": "audio-cpp/audio.cpp-gguf",
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"revision": "main",
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"gated": false
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}
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},
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"packages": [
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{
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"id": "whistle_asr_f32",
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"display_name": "Whistle ASR GGUF F32",
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"default": true,
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"format": "gguf",
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"precision": "f32",
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"target_directory": "Whistle-GGUF",
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"files": [
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"Whistle-GGUF/whistle-f32.gguf"
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],
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"strip_prefix": "Whistle-GGUF"
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}
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],
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"dependencies": [],
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"ui": {
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"tags": [
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"ASR",
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"GGUF"
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],
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"docs": [
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"docs/models/whistle_asr.md"
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],
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"recommended_package": "whistle_asr_f32"
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},
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"sources": [
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{
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"format": "gguf",
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"roots": {
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"model": ".",
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"weights": "$gguf"
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},
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"files": {
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"config": "model:config.json",
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"tokenizer_blob": "model:tokenizer.blob",
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"mel_filterbank": "model:mel_filterbank_80.f32",
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"hadamard_perm1": "model:hadamard_perm1.f32",
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"hadamard_perm2": "model:hadamard_perm2.f32"
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},
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"tensors": {
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"weights": "weights:"
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}
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},
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{
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"format": "safetensors",
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"roots": {
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"model": "."
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},
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"files": {
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"config": "model:config.json",
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"tokenizer_blob": "model:tokenizer.blob",
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"mel_filterbank": "model:mel_filterbank_80.f32",
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"hadamard_perm1": "model:hadamard_perm1.f32",
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"hadamard_perm2": "model:hadamard_perm2.f32"
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},
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"tensors": {
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"weights": "model:whistle.safetensors"
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}
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}
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]
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}
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