Decoding the logits provided by a tiny Wav2vec2 model gives sequences that do not make sense
Hello,I am trying to run Wav2Vec2 on a Raspberry Pi.I did it with the model ‘facebook/wav2vec2-base-960h’, but the computational time of the logits by the model is very long (12 seconds for a 2.6 seconds audio).So I looked for a smaller model, and I found “wav2vec2_tiny_random_robust” provided by Patrick von Platen on the hub (patrickvonplaten/wav2vec2_tiny_random_robust · Hugging Face), trained on librispeech_asr.However when I use this model and the associated tokenizer, it does not work:[‘fagfed dbabeaa ggbe gea b abf’]instead of [‘LY EVIDENT THAT THE TIME FOR AN INQUIRY WILL COME’] with the ‘base’ model.On the web page of the “tiny” model, the calculus of the cost function is provided, but not the way to decode the letter sequence.Is this a tokenizer problem or do I need to fine-tune the model?