Automatic Speech Recognition
Transformers
PyTorch
JAX
Fon
wav2vec2
audio
speech
xlsr-fine-tuning-week
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use chrisjay/fonxlsr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chrisjay/fonxlsr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="chrisjay/fonxlsr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("chrisjay/fonxlsr") model = AutoModelForCTC.from_pretrained("chrisjay/fonxlsr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test/test_fon_1037.json from chrisjay/fonxlsr: direct link, hf CLI and curl.
- Browser
- Download file 132 Bytes
-
https://huggingface.co/chrisjay/fonxlsr/resolve/refs%2Fpr%2F1/test/test_fon_1037.json
- Command line
-
hf download hf://chrisjay/fonxlsr@refs/pr/1/test/test_fon_1037.json
-
curl -L -o test_fon_1037.json https://huggingface.co/chrisjay/fonxlsr/resolve/refs%2Fpr%2F1/test/test_fon_1037.json
132 Bytes
| {"path": "./FonAudio/pyFongbe-master/data/test/wav/helmut/helmut_fongbe_corp004_044.wav", "sentence": "mi na kpe go gbe \u0256okpo"} |