Instructions to use hf-tiny-model-private/tiny-random-SpeechT5Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-SpeechT5Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-SpeechT5Model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SpeechT5Model") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-SpeechT5Model") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "</s>", | |
| "model_max_length": 450, | |
| "pad_token": "<pad>", | |
| "processor_class": "SpeechT5Processor", | |
| "sp_model_kwargs": {}, | |
| "special_tokens_map_file": "/home/runner/.cache/huggingface/hub/models--microsoft--speecht5_asr/snapshots/53615c10408485422e09a12cda191a747f4bbe34/special_tokens_map.json", | |
| "tokenizer_class": "SpeechT5Tokenizer", | |
| "unk_token": "<unk>" | |
| } | |