---

license: apache-2.0

language:

• ja
• en
• zh

tags:

• asr
• speech-recognition
• gguf
• qwen3

base_model: jaykwok/Qwen3-ASR-1.7B-JA-Anime-Galgame-hf

pipeline_tag: automatic-speech-recognition

---

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

GGUF quantizations of jaykwok/Qwen3-ASR-1.7B-JA-Anime-Galgame-hf for use with CrispASR.

This is a Japanese anime/galgame fine-tune of Qwen3-ASR-1.7B. It supports 30+ languages with enhanced performance on Japanese anime/game speech.

Files

| File | Quant | Size | Notes |

|------|-------|------|-------|

| qwen3-asr-1.7b-ja-anime-q4_k.gguf | Q4_K | ~1.3 GB | Recommended for most use cases |

| qwen3-asr-1.7b-ja-anime-q8_0.gguf | Q8_0 | ~2.5 GB | Higher quality, more memory |

Usage with CrispASR

# 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:

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.