Instructions to use eustlb/higgs-v2-archive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eustlb/higgs-v2-archive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="eustlb/higgs-v2-archive")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("eustlb/higgs-v2-archive") model = AutoModelForTextToWaveform.from_pretrained("eustlb/higgs-v2-archive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from eustlb/higgs-v2-archive: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/eustlb/higgs-v2-archive/resolve/main/tokenizer.json
- Command line
-
hf download hf://eustlb/higgs-v2-archive/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/eustlb/higgs-v2-archive/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 9948c75f9c14d166652dee38424d77d62b7090c7c52df3c10451310d52f9a556
- Size of remote file:
- 17.2 MB
- SHA256:
- 1a222563314bf6ffe3471622bff017ff5bb0630f2924faf44216195ebfef2af3
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