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---
license: apache-2.0
datasets:
- asierhv/composite_corpus_eu_v2.1
language:
- eu
metrics:
- wer
model-index:
- name: Whisper Base Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 18.0
type: mozilla-foundation/common_voice_18_0
config: eu
split: test
args:
language: eu
metrics:
- name: Test WER
type: wer
value: 10.78
base_model:
- xezpeleta/whisper-base-eu
---
# Whisper Basque (eu) - CTranslate2 Conversion (int8)
**This is a CTranslate2 conversion of [xezpeleta/whisper-base-eu](https://huggingface.co./xezpeleta/whisper-base-eu) designed for use with faster-whisper.**
## Model Details
- **Base Model:** OpenAI Whisper Base (original model card: [whisper-base](https://huggingface.co./openai/whisper-base))
- **Finetuned for:** Basque (eu) speech recognition
- **Dataset:** `asierhv/composite_corpus_eu_v2.1` (Mozilla Common Voice 18.0 + Basque Parliament + OpenSLR)
- **Conversion Format:** CTranslate2 (optimized for inference)
- **Compatibility:** Designed for use with [faster-whisper](https://github.com/SYSTRAN/faster-whisper)
- **Quantization:** int8 (ready for CPU inference)
- **WER:** 10.78% on Mozilla Common Voice 18.0
## Usage with faster-whisper
First install required packages:
```bash
pip install faster-whisper
```
Then use the following code snippet:
```py
from faster_whisper import WhisperModel
# Load the model (FP16 precision)
model = WhisperModel("xezpeleta/whisper-base-eu-ct2", device="cuda", compute_type="float16")
# Transcribe audio file
segments, info = model.transcribe("audio.mp3", language="eu")
# Print transcription
for segment in segments:
print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
```
## Evaluation
The model achieves **10.78% Word Error Rate (WER)** on the Basque `test` split of **Mozilla Common Voice 18.0**.
# Conversion details
Converted from the original HuggingFace model using:
```bash
ct2-transformers-converter --model xezpeleta/whisper-base-eu \
--output_dir whisper-base-eu-ct2 \
--copy_files tokenizer.json preprocessor_config.json \
--quantization float16
```
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