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sengtha
iAny
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Publish dataset to Hugging Face
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Publish dataset to Hugging Face
Publish dataset to Hugging Face
#3:
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sengtha
2m 26s
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2m 26s
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grove: signed fixtures for offline consumer development (CamboVerse)
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#55:
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grove: reference node (federated verify-on-ingest) + CamboVerse bridge
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#54:
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grove: /garden capture flow — create signed observations on-device
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#53:
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grove: decentralized verifiable garden-observation protocol (v1)
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#52:
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docs: add dataset card for sengtha/khmer-qa
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#51:
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docs: add Hugging Face model cards (whisper-base-khmer, iany-waste-v1)
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#50:
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docs: reflect new models (whisper-base-khmer STT, iany-waste-v1)
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#49:
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waste-scan: add /waste-scan try-it experiment (live material detector)
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#48:
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ci: use Wrangler 4 (config needs run_worker_first array form)
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#47:
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ci: fix Cloudflare deploy — pin Wrangler 3.x that reads wrangler.jsonc
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#46:
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waste: wire the real trained model (ONNX) into the live camera
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#45:
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docs(waste-model): note techsash/waste-classification-data (binary O/R)
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#44:
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docs(waste-model): add Kaggle training path (§3B)
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#43:
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stt: capture mic at 16 kHz directly (anti-aliased) for cleaner ASR input
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#42:
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scripts(eval_stt): raise max_new_tokens 225->448 (Khmer is token-dense)
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#41:
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scripts(eval_stt): use jiwer directly instead of evaluate
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#40:
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scripts(eval_stt): support local model + load_from_disk dataset (CPU/…
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#39:
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scripts: add reusable eval_stt.py (fresh-pod STT quality test)
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#38:
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app: full-width desktop layout + strip STT replacement-char boxes
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#37:
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stt: point PWA Khmer STT at whisper-base-khmer
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#36:
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docs(stt): fix GGML convert — save WhisperProcessor first (vocab.json)
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#35:
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docs(stt): fix whisper.cpp binary names (whisper-quantize, whisper-cli)
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#34:
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label: read barcode + ច.ប.ផ code from one photo
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#33:
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label: /label reader — read the ច.ប.ផ registration code (no training)
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#32:
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