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
Update config.json
Browse files- config.json +0 -7
config.json
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"pad_token_id": 128001,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 32.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"transformers_version": "4.57.0.dev0",
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"pad_token_id": 128001,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"transformers_version": "4.57.0.dev0",
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