Model Details
Full Model IDkingabzpro/wav2vec2-large-xls-r-300m-Urdu
Pipeline / Taskautomatic-speech-recognition
Librarytransformers
Downloads (all-time)2.3M
Likes13
Last Modified6/24/2026
Author / Orgkingabzpro
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="kingabzpro/wav2vec2-large-xls-r-300m-Urdu")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorswav2vec2automatic-speech-recognitiongenerated_from_trainerhf-asr-leaderboardrobust-speech-eventurdataset:mozilla-foundation/common_voice_8_0base_model:facebook/wav2vec2-xls-r-300mbase_model:finetune:facebook/wav2vec2-xls-r-300mlicense:apache-2.0model-indexendpoints_compatibleregion: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
⬇ Downloads2.3M
❤️ Community Likes13
🛠️ 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.