Downloads · 30 days
56
11% of all-time downloads
wav2vec2-large-960h-GGUF
liodon-ai/wav2vec2-large-960h-GGUF
wav2vec2-large-960h-GGUF is a machine learning model from liodon-ai. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for wav2vec2.cpp. The card lists the license as other.
GGUF quantizations of facebook/wav2vec2-large-960h for use with wav2vec2.cpp.
All-time downloads
509
Public
Repo size
1.2 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.gguf1.2 GB · 100%
At a glance
- Library
- wav2vec2.cpp
- License
- other
- Access
- Public
- Created
- Jun 28, 2026
- Updated
- Jun 28, 2026
- SHA
- d6841317
Base models
Model card
From the Hugging Face model README
wav2vec2-large-960h
GGUF quantizations of facebook/wav2vec2-large-960h for use with wav2vec2.cpp.
Files
| Filename | Quant | Size | Precision |
|---|---|---|---|
model_f16.gguf | F16 | 631 MB | ~fp16 (near-lossless) |
model_q8_0.gguf | Q8_0 | 373 MB | 8-bit quantized linear layers |
model_q4_0.gguf | Q4_0 | 222 MB | 4-bit quantized linear layers |
Parity vs HuggingFace Reference
Tested on 10 audio samples from LibriSpeech.
| Quant | Mean CER (vs HF) | Mean WER (vs HF) | Status |
|---|---|---|---|
| F16 | 0.14% | 0.83% | PASS |
| Q8_0 | 0.43% | 3.23% | PASS |
| Q4_0 | 0.67% | 2.59% | PASS |
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-960h-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: facebook/wav2vec2-large-960h
- Architecture: large-960h
- Language: en
- Task: Automatic Speech Recognition
Conversion
Converted using wav2vec2.cpp scripts/convert_to_gguf.py.
python scripts/convert_to_gguf.py facebook/wav2vec2-large-960h model_f16.gguf --dtype f16
python scripts/convert_to_gguf.py facebook/wav2vec2-large-960h model_q8_0.gguf --dtype q8_0
python scripts/convert_to_gguf.py facebook/wav2vec2-large-960h model_q4_0.gguf --dtype q4_0
License
Follows the license of the source model.
- Library
- wav2vec2.cpp
- License
- other
- Languages
- en
- Created
- Jun 28, 2026
- Updated
- Jun 28, 2026