Instructions to use declare-lab/tango2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use declare-lab/tango2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="declare-lab/tango2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("declare-lab/tango2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vae_config.json from declare-lab/tango2: direct link, hf CLI and curl.
- Browser
- Download file 326 Bytes
-
https://huggingface.co/declare-lab/tango2/resolve/main/vae_config.json
- Command line
-
hf download hf://declare-lab/tango2/vae_config.json
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curl -L -o vae_config.json https://huggingface.co/declare-lab/tango2/resolve/main/vae_config.json
326 Bytes
| {"image_key": "fbank", "subband": 1, "embed_dim": 8, "time_shuffle": 1, "ddconfig": {"double_z": true, "z_channels": 8, "resolution": 256, "downsample_time": false, "in_channels": 1, "out_ch": 1, "ch": 128, "ch_mult": [1, 2, 4], "num_res_blocks": 2, "attn_resolutions": [], "dropout": 0.0}, "scale_factor": 0.9227914214134216} |