Automatic Speech Recognition
Transformers
PyTorch
Safetensors
English
bart
text2text-generation
audio
speech
asr
hubert
Instructions to use voidful/tts_hubert_cluster_bart_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/tts_hubert_cluster_bart_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="voidful/tts_hubert_cluster_bart_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("voidful/tts_hubert_cluster_bart_base") model = AutoModelForSeq2SeqLM.from_pretrained("voidful/tts_hubert_cluster_bart_base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19a735f244956fbb1b945159c1c5fc995544ddb91306dd7d7f21ef1c43f0c012
- Size of remote file:
- 715 MB
- SHA256:
- 7c46d429349ffa5acb12d8a596f047f3ff376e8959a927773347350e4bb50e4b
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