wav2vec2 base 100k voxpopuli

Introduction

The Wav2Vec2-Base-100K-VoxPopuli model by Facebook is a pre-trained automatic speech recognition model. It is based on the Wav2Vec2 architecture and has been trained on the 100,000 unlabeled subset of the VoxPopuli corpus. The model is designed to learn the structure of speech directly from raw audio data. However, it requires further fine-tuning for specific applications, as it does not include a tokenizer.

Architecture

The model leverages the Wav2Vec2 architecture, which is centered on learning speech representations from raw audio inputs. The model operates without a tokenizer, focusing purely on audio-based training. This design supports various applications in automatic speech recognition and multilingual audio processing.

Training

The Wav2Vec2-Base-100K-VoxPopuli model was pre-trained on a large-scale multilingual speech corpus known as VoxPopuli. The model's training involves learning from 100,000 hours of unlabeled audio data, enabling it to capture diverse speech patterns. For practical deployment, users must fine-tune the model with labeled text data. Instructions and further guidance on fine-tuning are available in the Hugging Face blog.

Guide: Running Locally

To run the Wav2Vec2-Base-100K-VoxPopuli model locally, follow these steps:

1. Install Dependencies: Ensure you have Python and PyTorch installed. Install the Transformers library using pip:

   pip install transformers
   

2. Load the Model: Use the Hugging Face Transformers library to load the pre-trained model:

   from transformers import Wav2Vec2ForPreTraining, Wav2Vec2Tokenizer
   
   model = Wav2Vec2ForPreTraining.from_pretrained("facebook/wav2vec2-base-100k-voxpopuli")
   

3. Fine-Tune the Model: As the model is pre-trained on audio only, you will need to fine-tune it with labeled data and create a tokenizer. Refer to the Hugging Face fine-tuning guide for detailed instructions.

4. Consider Cloud GPUs: For efficient training and inference, especially with large datasets, consider using cloud-based GPUs from providers like AWS, Google Cloud, or Azure.

License

The Wav2Vec2-Base-100K-VoxPopuli model is released under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). This permits use, sharing, and adaptation for non-commercial purposes, provided appropriate credit is given.