Instructions to use hf-internal-testing/tiny-random-SpeechT5Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SpeechT5Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-SpeechT5Model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SpeechT5Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SpeechT5Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 407 Bytes
7b248f7 | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"bos_token": "<s>",
"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/c5ef64c71905caeccde0e4462ef3f9077224c524/special_tokens_map.json",
"tokenizer_class": "SpeechT5Tokenizer",
"unk_token": "<unk>"
}
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