kingabzpro/wav2vec2-large-xls-r-300m-Urdu
automatic-speech-recognition model by kingabzpro
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Model card & documentation
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A fine-tuned XLS-R 300M CTC model for Urdu automatic speech recognition. It transcribes 16 kHz mono audio and includes an optional 5-gram KenLM decoder. Best reported result: 39.89% WER / 16.70% CER with KenLM decoding on the Urdu Common Voice 8.0 test set. See the Kaggle evaluation notebook for a reproducible example. Install the required packages: Transcribe a local audio file: Show the complete KenLM decoding example The repository contains a 5-gram KenLM language model. The Kaggle notebook evaluates a five-sample streaming smoke test from fixie-ai/commonvoice170 (ur, test). Show the core evaluation code Single-sample inference: Five-sample streaming smoke-test results: Results are reported on the Urdu test split of Mozilla Common Voice…
Read the full model card ↗ · Preview checked 2026-10-29T16:13:33.018Z
Inside the original model card — Document outline
- Urdu ASR XLS-R 300M
- ⚡ Quick start
- 🧠 Language-model decoding
- 🧪 Kaggle evaluation
- Recorded notebook output
- 📊 Evaluation
- Full Common Voice 8.0 test set
- 🏗️ Training
- ⚠️ Intended use and limitations
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
kingabzpro/wav2vec2-large-xls-r-300m-Urdu is a automatic-speech-recognition model repository published by kingabzpro on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- automatic-speech-recognition
- Library
- transformers
- Recent downloads (30 days)
- 1,271,220
- Cumulative likes
- 24
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 315,497,145
- Architecture
- Wav2Vec2ForCTC
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2022-03-02T23:29:05.000Z
- Last modified
- 2026-06-24T16:02:52.000Z
Compatibility and lineage
Reported languages: ur
Reported base models: facebook/wav2vec2-xls-r-300m
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:51:32.899Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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