# Auto-download and transcribe
crispasr -m qwen3-ja-anime -f audio.wav

# Or specify the model path directly
crispasr -m qwen3-asr-1.7b-ja-anime-q4_k.gguf -f audio.wav --backend qwen3

Conversion

Converted from safetensors using:

bash

python models/convert-qwen3-asr-to-gguf.py \
    --input jaykwok/Qwen3-ASR-1.7B-JA-Anime-Galgame-hf \
    --output qwen3-asr-1.7b-ja-anime-f16.gguf
crispasr-quantize qwen3-asr-1.7b-ja-anime-f16.gguf qwen3-asr-1.7b-ja-anime-q4_k.gguf q4_k

Architecture

Same as Qwen3-ASR-1.7B:

Audio encoder: 24-layer Whisper-style encoder (d=1024, 16 heads)
Projector: 2-layer MLP (1024 → GELU → 2048)
LLM decoder: 28-layer Qwen3 (d=2048, 16Q/8KV heads, SwiGLU)
Vocab: 151,936 tokens (GPT-2 BPE)

License

Apache 2.0 (following the base model license)

Provenance and EU AI Act Art. 53 note

Upstream model: jaykwok/Qwen3-ASR-1.7B-JA-Anime-Galgame-hf — published by jaykwok.
Upstream licence: apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.

cstr/qwen3-asr-1.7b-ja-anime-GGUF

Qwen3-ASR-1.7B-JA-Anime-Galgame — GGUF

Files

Usage with CrispASR

Conversion

Architecture

License

Provenance and EU AI Act Art. 53 note

cstr/
qwen3-asr-1.7b-ja-anime-GGUF