Model Details
Full Model IDjonatasgrosman/wav2vec2-large-xlsr-53-russian
Pipeline / Taskautomatic-speech-recognition
Librarytransformers
Downloads (all-time)4.3M
Likes77
Last Modified12/14/2022
Author / Orgjonatasgrosman
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-russian")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchjaxwav2vec2automatic-speech-recognitionaudiohf-asr-leaderboardmozilla-foundation/common_voice_6_0robust-speech-eventruspeechxlsr-fine-tuning-weekdataset:common_voicedataset:mozilla-foundation/common_voice_6_0doi:10.57967/hf/3571license:apache-2.0model-indexendpoints_compatibledeploy:azureregion:us
More Speech Recognition Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🎙️ Task: Speech Recognition
This model is designed for the Speech Recognition task. Explore more models for this use case.
All Speech Recognition Models →📊 Popularity
⬇ Downloads4.3M
❤️ Community Likes77
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.