lucataco/magnet ❓🔢📝 → 🖼️
About
MAGNeT: Masked Audio Generation using a Single Non-Autoregressive Transformer

Example Output
Prompt:
"80s electronic track with melodic synthesizers, catchy beat and groovy bass"
Output
Performance Metrics
14.64s
Prediction Time
110.30s
Total Time
All Input Parameters
{ "model": "facebook/magnet-small-10secs", "top_p": 0.9, "prompt": "80s electronic track with melodic synthesizers, catchy beat and groovy bass", "max_cfg": 10, "min_cfg": 1, "span_score": "prod-stride1", "variations": 3, "temperature": 3, "decoding_steps_stage_1": 20, "decoding_steps_stage_2": 10, "decoding_steps_stage_3": 10, "decoding_steps_stage_4": 10 }
Input Parameters
- model
- Model to use
- top_p
- Top p for sampling
- prompt
- Input Text
- max_cfg
- Max CFG coefficient
- min_cfg
- Min CFG coefficient
- span_score
- variations
- Number of variations to generate
- temperature
- Temperature for sampling
- decoding_steps_stage_1
- Number of decoding steps for stage 1
- decoding_steps_stage_2
- Number of decoding steps for stage 2
- decoding_steps_stage_3
- Number of decoding steps for stage 3
- decoding_steps_stage_4
- Number of decoding steps for stage 4
Output Schema
Output
Example Execution Logs
/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm. warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.") spiece.model: 0%| | 0.00/792k [00:00<?, ?B/s] spiece.model: 100%|██████████| 792k/792k [00:00<00:00, 31.9MB/s] tokenizer.json: 0%| | 0.00/1.39M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 1.39M/1.39M [00:00<00:00, 24.7MB/s] config.json: 0%| | 0.00/1.21k [00:00<?, ?B/s] config.json: 100%|██████████| 1.21k/1.21k [00:00<00:00, 10.4MB/s] model.safetensors: 0%| | 0.00/892M [00:00<?, ?B/s] model.safetensors: 4%|▎ | 31.5M/892M [00:00<00:05, 171MB/s] model.safetensors: 7%|▋ | 62.9M/892M [00:00<00:04, 193MB/s] model.safetensors: 11%|█ | 94.4M/892M [00:00<00:03, 208MB/s] model.safetensors: 14%|█▍ | 126M/892M [00:00<00:03, 231MB/s] model.safetensors: 18%|█▊ | 157M/892M [00:00<00:03, 213MB/s] model.safetensors: 22%|██▏ | 199M/892M [00:00<00:03, 227MB/s] model.safetensors: 26%|██▌ | 231M/892M [00:01<00:02, 232MB/s] model.safetensors: 29%|██▉ | 262M/892M [00:01<00:02, 234MB/s] model.safetensors: 33%|███▎ | 294M/892M [00:01<00:02, 235MB/s] model.safetensors: 36%|███▋ | 325M/892M [00:01<00:02, 239MB/s] model.safetensors: 40%|███▉ | 357M/892M [00:01<00:02, 233MB/s] model.safetensors: 44%|████▎ | 388M/892M [00:01<00:02, 233MB/s] model.safetensors: 47%|████▋ | 419M/892M [00:01<00:02, 235MB/s] model.safetensors: 51%|█████ | 451M/892M [00:01<00:01, 236MB/s] model.safetensors: 54%|█████▍ | 482M/892M [00:02<00:01, 227MB/s] model.safetensors: 58%|█████▊ | 514M/892M [00:02<00:01, 229MB/s] model.safetensors: 61%|██████ | 545M/892M [00:02<00:01, 228MB/s] model.safetensors: 65%|██████▍ | 577M/892M [00:02<00:01, 230MB/s] model.safetensors: 68%|██████▊ | 608M/892M [00:02<00:01, 238MB/s] model.safetensors: 72%|███████▏ | 640M/892M [00:02<00:01, 246MB/s] model.safetensors: 75%|███████▌ | 671M/892M [00:02<00:00, 245MB/s] model.safetensors: 79%|███████▉ | 703M/892M [00:03<00:00, 244MB/s] model.safetensors: 82%|████████▏ | 734M/892M [00:03<00:00, 242MB/s] model.safetensors: 86%|████████▌ | 765M/892M [00:03<00:00, 175MB/s] model.safetensors: 88%|████████▊ | 786M/892M [00:03<00:00, 155MB/s] model.safetensors: 92%|█████████▏| 818M/892M [00:03<00:00, 175MB/s] model.safetensors: 95%|█████████▌| 849M/892M [00:03<00:00, 190MB/s] model.safetensors: 99%|█████████▉| 881M/892M [00:04<00:00, 200MB/s] model.safetensors: 100%|██████████| 892M/892M [00:04<00:00, 217MB/s]
Version Details
- Version ID
e8e2ecd4a1dabb58924aa8300b668290cafae166dd36baf65dad9875877de50e
- Version Created
- January 17, 2024