Q4_K_M GGUF (~2.4 GB) of the merged gemma-3-4b-it-voice-digest LoRA: a WhatsApp-voice-note digester for Hindi / Hinglish / Tamil / Bengali that emits schema-exact JSON (English summary, translation, confirmed|tentative action items — empty list for pure chat). Runs on llama.cpp anywhere, including phones; ~25 s per note on an 8 GB M2 Air, all offline.

See the adapter card for the required prompt format (system prompt, From: {sender} line, and the three instruction variants that select full / no-translation / translation-only output), training data, and the full evaluation. Headline: end-to-end action-item F1 0.76, hallucination 0.10 on pure-chat notes, 0 schema-parse failures, measured through this exact quantized file with a JSON grammar.

Quick start (llama-cpp-python)

python

from llama_cpp import Llama
llm = Llama.from_pretrained("yashwork-byte/gemma-3-4b-it-voice-digest-GGUF",
                            "gemma-3-4b-it-ft-Q4_K_M.gguf", n_ctx=2048, n_gpu_layers=-1)
out = llm.create_chat_completion(
    messages=[{"role": "system", "content": SYSTEM_PROMPT},
              {"role": "user", "content": f"Digest this voice note transcript.\n\nFrom: Papa\n{transcript}"}],
    response_format={"type": "json_object"}, temperature=0.1)

Gemma derivative — subject to the Gemma Terms of Use.