Instructions to use Matthijs/mms-tts-abp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matthijs/mms-tts-abp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Matthijs/mms-tts-abp")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("Matthijs/mms-tts-abp") model = AutoModelForTextToWaveform.from_pretrained("Matthijs/mms-tts-abp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from Matthijs/mms-tts-abp: direct link, hf CLI and curl.
- Browser
- Download file 51 Bytes
-
https://huggingface.co/Matthijs/mms-tts-abp/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://Matthijs/mms-tts-abp/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/Matthijs/mms-tts-abp/resolve/main/special_tokens_map.json
51 Bytes
| { | |
| "pad_token": "<pad>", | |
| "unk_token": "<unk>" | |
| } | |