Model Details
Full Model IDfacebook/wav2vec2-base-960h
Pipeline / Taskautomatic-speech-recognition
Librarytransformers
Downloads (all-time)1.2M
Likes396
Last Modified11/14/2022
Author / Orgfacebook
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="facebook/wav2vec2-base-960h")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchtfsafetensorswav2vec2automatic-speech-recognitionaudiohf-asr-leaderboardendataset:librispeech_asrarxiv:2006.11477license:apache-2.0model-indexeval-resultsendpoints_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
⬇ Downloads1.2M
❤️ Community Likes396
🛠️ 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.