Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
English
wav2vec2
voxpopuli
google/xtreme_s
Generated from Trainer
Instructions to use anton-l/xtreme_s_xlsr_300m_voxpopuli_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anton-l/xtreme_s_xlsr_300m_voxpopuli_en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="anton-l/xtreme_s_xlsr_300m_voxpopuli_en")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("anton-l/xtreme_s_xlsr_300m_voxpopuli_en") model = AutoModelForCTC.from_pretrained("anton-l/xtreme_s_xlsr_300m_voxpopuli_en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download emissions.csv from anton-l/xtreme_s_xlsr_300m_voxpopuli_en: direct link, hf CLI and curl.
- Browser
- Download file 302 Bytes
-
https://huggingface.co/anton-l/xtreme_s_xlsr_300m_voxpopuli_en/resolve/main/emissions.csv
- Command line
-
hf download hf://anton-l/xtreme_s_xlsr_300m_voxpopuli_en/emissions.csv
-
curl -L -o emissions.csv https://huggingface.co/anton-l/xtreme_s_xlsr_300m_voxpopuli_en/resolve/main/emissions.csv
302 Bytes
| timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region | |
| 2022-04-30T05:41:49,73faf8c7-0d8f-4642-a86a-4d1bdbeeb9d1,codecarbon,38596.32709336281,8.977324439459553,15.852594807451094,USA,USA,Iowa,Y,gcp,us-central1 | |