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")# pip install -U transformers accelerate # 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 valid/valid_fon_10.json from chrisjay/fonxlsr: direct link, hf CLI and curl.
- Browser
- Download file 152 Bytes
-
https://huggingface.co/chrisjay/fonxlsr/resolve/70fb3c1900033a48ac15cedfe244dcc45889c03d/valid/valid_fon_10.json
- Command line
-
hf download hf://chrisjay/fonxlsr@70fb3c1900033a48ac15cedfe244dcc45889c03d/valid/valid_fon_10.json
-
curl -L -o valid_fon_10.json https://huggingface.co/chrisjay/fonxlsr/resolve/70fb3c1900033a48ac15cedfe244dcc45889c03d/valid/valid_fon_10.json
152 Bytes
| {"path": "./FonAudio/pyFongbe-master/data/test/wav/antoine/antoine_fongbe_corp000_017.wav", "sentence": "gbe \u0256e gbe \u0254 un na wa g\u0254n towe"} |