microsoft/wavlm-large
feature-extraction model by microsoft
From the publisher
Model card & documentation
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Microsoft's WavLM The large model pretrained on 16kHz sampled speech audio. When using the model, make sure that your speech input is also sampled at 16kHz. Note: This model does not have a tokenizer as it was pretrained on audio alone. In order to use this model speech recognition, a tokenizer should be created and the model should be fine-tuned on labeled text data. Check out this blog for more in-detail explanation of how to fine-tune the model. The model was pre-trained on: Paper: WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing Authors: Sanyuan Chen, Chengyi Wang, Zhengyang Chen, Yu Wu, Shujie Liu, Zhuo Chen, Jinyu Li, Naoyuki Kanda, Takuya Yoshioka, Xiong Xiao, Jian Wu, Long Zhou, Shuo Ren, Yanmin Qian, Yao Qian, Jian Wu, Michael Zeng, Furu Wei Abstract Self-supervised learning (SSL) achieves great success in speech recognition, while limited exploration has been attempted for other speech processing…
Read the full model card ↗ · Preview checked 2026-10-30T12:08:30.112Z
Inside the original model card — Document outline
- WavLM-Large
- Usage
- Speech Recognition
- Speech Classification
- Speaker Verification
- Speaker Diarization
- Contribution
- License
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Model overview
microsoft/wavlm-large is a feature-extraction model repository published by microsoft 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
- feature-extraction
- Library
- transformers
- Recent downloads (30 days)
- 1,068,711
- Cumulative likes
- 122
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- WavLMModel
- License
- Not reported — check the model card
- Access
- Not gated by Hugging Face
- Created
- 2022-03-02T23:29:05.000Z
- Last modified
- 2022-02-02T21:21:50.000Z
Compatibility and lineage
Reported languages: en
Base-model lineage was not included.
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 2026-11-01T06:54:29.511Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.