Instructions to use AJosh/modelclone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AJosh/modelclone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="AJosh/modelclone")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("AJosh/modelclone") model = AutoModelForTextToWaveform.from_pretrained("AJosh/modelclone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
File size: 361 Bytes
3281f89 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"attn_implementation": "sdpa",
"bos_token_id": 128000,
"depth_decoder_do_sample": true,
"depth_decoder_max_new_tokens": 31,
"depth_decoder_min_new_tokens": 31,
"depth_decoder_temperature": 0.9,
"do_sample": true,
"max_length": 2048,
"max_new_tokens": 125,
"pad_token_id": 128256,
"temperature": 0.9,
"transformers_version": "4.52.3"
}
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