liodon-ai/wav2vec2-large-xlsr-53-chinese-zh-cn-GGUF overview
wav2vec2 large xlsr 53 chinese zh cn GGUF quantizations of jonatasgrosman/wav2vec2 large xlsr 53 chinese zh cn https://huggingface.co/jonatasgrosman/wav2vec2 l…
Runs locally from ~213.6 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
Model README
---
language:
- zh
license: other
tags:
- wav2vec2
- gguf
- asr
- speech
- audio
library_name: wav2vec2.cpp
base_model:
- jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn
---
wav2vec2-large-xlsr-53-chinese-zh-cn
GGUF quantizations of jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn for use with wav2vec2.cpp.
Files
| Filename | Quant | Size | Precision |
|----------|-------|------|-----------|
| model_f16.gguf | F16 | 638 MB | ~fp16 (near-lossless) |
| model_q8_0.gguf | Q8_0 | 377 MB | 8-bit quantized linear layers |
| model_q4_0.gguf | Q4_0 | 224 MB | 4-bit quantized linear layers |
Parity vs HuggingFace Reference
Tested on 10 audio samples from FLEURS cmn_hans_cn.
| Quant | Mean CER (vs HF) | Mean WER (vs HF) | Status |
|-------|-----------------|-----------------|--------|
| F16 | 0.50% | 25.00% | PASS |
| Q8_0 | 1.31% | 37.50% | PASS |
| Q4_0 | 6.96% | 87.50% | FAIL |
CER/WER measured against HF model output (not ground truth) to isolate quantization error.
Usage
C++ CLI
# Clone and build
git clone --recursive https://github.com/liodon-ai/wav2vec2.cpp
cd wav2vec2.cpp && mkdir build && cd build && cmake .. && make -j
# Download and run
huggingface-cli download liodon-ai/wav2vec2-large-xlsr-53-chinese-zh-cn-GGUF model_q8_0.gguf --local-dir .
./wav2vec2-cli -m model_q8_0.gguf -f audio.wav
# With word timestamps
./wav2vec2-cli -m model_q8_0.gguf -f audio.wav -w
# SRT subtitle output
./wav2vec2-cli -m model_q8_0.gguf -f audio.wav --format srt > output.srt
Python (via subprocess)
import subprocess, json
result = subprocess.run(
['./wav2vec2-cli', '-m', 'model_q8_0.gguf', '-f', 'audio.wav', '--format', 'json'],
capture_output=True, text=True
)
data = json.loads(result.stdout)
print(data['transcript'])
Source Model
- Original: jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn
- Architecture: XLS-R
- Language: zh
- Task: Automatic Speech Recognition
Conversion
Converted using wav2vec2.cpp scripts/convert_to_gguf.py.
python scripts/convert_to_gguf.py jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn model_f16.gguf --dtype f16
python scripts/convert_to_gguf.py jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn model_q8_0.gguf --dtype q8_0
python scripts/convert_to_gguf.py jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn model_q4_0.gguf --dtype q4_0
License
Follows the license of the source model.
Run liodon-ai/wav2vec2-large-xlsr-53-chinese-zh-cn-GGUF with guIDE
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Source: Hugging Face · Compare models