ttsds / fishspeech_1_1
The Fish Speech V1.1 model.
Prediction
ttsds/fishspeech_1_1:eba2a3e1e07cf38ac2a528d134fdac1cab4d222b8850ac98517635ddf5c1ca75IDfgdgr9djqxrme0cmnpx9bhp1emStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- text
- With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.
- text_reference
- and keeping eternity before the eyes, though much
- speaker_reference
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
{ "text": "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.", "text_reference": "and keeping eternity before the eyes, though much", "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run ttsds/fishspeech_1_1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ttsds/fishspeech_1_1:eba2a3e1e07cf38ac2a528d134fdac1cab4d222b8850ac98517635ddf5c1ca75", { input: { text: "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.", text_reference: "and keeping eternity before the eyes, though much", speaker_reference: "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun ttsds/fishspeech_1_1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ttsds/fishspeech_1_1:eba2a3e1e07cf38ac2a528d134fdac1cab4d222b8850ac98517635ddf5c1ca75", input={ "text": "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.", "text_reference": "and keeping eternity before the eyes, though much", "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run ttsds/fishspeech_1_1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "ttsds/fishspeech_1_1:eba2a3e1e07cf38ac2a528d134fdac1cab4d222b8850ac98517635ddf5c1ca75", "input": { "text": "With tenure, Suzie\'d have all the more leisure for yachting, but her publications are no good.", "text_reference": "and keeping eternity before the eyes, though much", "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
{ "completed_at": "2025-01-28T16:26:05.034677Z", "created_at": "2025-01-28T16:24:41.407000Z", "data_removed": false, "error": null, "id": "fgdgr9djqxrme0cmnpx9bhp1em", "input": { "text": "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.", "text_reference": "and keeping eternity before the eyes, though much", "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav" }, "logs": "2025-01-28 16:26:02.222 | INFO | tools.llama.generate:generate_long:491 - Encoded text: With tenure, Suzie'd have all\n2025-01-28 16:26:02.222 | INFO | tools.llama.generate:generate_long:491 - Encoded text: the more leisure for yachting,\n2025-01-28 16:26:02.222 | INFO | tools.llama.generate:generate_long:491 - Encoded text: but her publications are no\n2025-01-28 16:26:02.222 | INFO | tools.llama.generate:generate_long:491 - Encoded text: good.\n2025-01-28 16:26:02.223 | INFO | tools.llama.generate:generate_long:509 - Generating sentence 1/4 of sample 1/1\n 0%| | 0/1858 [00:00<?, ?it/s]/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/backends/cuda/__init__.py:342: FutureWarning: torch.backends.cuda.sdp_kernel() is deprecated. In the future, this context manager will be removed. Please see, torch.nn.attention.sdpa_kernel() for the new context manager, with updated signature.\nwarnings.warn(\n 0%| | 6/1858 [00:00<00:31, 59.00it/s]\n 1%| | 12/1858 [00:00<00:32, 57.47it/s]\n 1%| | 19/1858 [00:00<00:30, 60.07it/s]\n 1%|▏ | 26/1858 [00:00<00:29, 61.43it/s]\n 2%|▏ | 33/1858 [00:00<00:29, 62.05it/s]\n 2%|▏ | 40/1858 [00:00<00:29, 62.57it/s]\n 3%|▎ | 47/1858 [00:00<00:29, 62.38it/s]\n3%|▎ | 49/1858 [00:00<00:29, 60.40it/s]\n2025-01-28 16:26:03.118 | INFO | tools.llama.generate:generate_long:565 - Generated 51 tokens in 0.90 seconds, 56.95 tokens/sec\n2025-01-28 16:26:03.118 | INFO | tools.llama.generate:generate_long:568 - Bandwidth achieved: 22.22 GB/s\n2025-01-28 16:26:03.118 | INFO | tools.llama.generate:generate_long:573 - GPU Memory used: 2.45 GB\n2025-01-28 16:26:03.119 | INFO | tools.llama.generate:generate_long:509 - Generating sentence 2/4 of sample 1/1\n 0%| | 0/1759 [00:00<?, ?it/s]\n 0%| | 7/1759 [00:00<00:27, 62.93it/s]\n 1%| | 14/1759 [00:00<00:27, 62.96it/s]\n 1%| | 21/1759 [00:00<00:27, 62.82it/s]\n 2%|▏ | 28/1759 [00:00<00:28, 61.75it/s]\n 2%|▏ | 35/1759 [00:00<00:27, 62.10it/s]\n2%|▏ | 40/1759 [00:00<00:28, 60.85it/s]\n2025-01-28 16:26:03.792 | INFO | tools.llama.generate:generate_long:565 - Generated 42 tokens in 0.67 seconds, 62.37 tokens/sec\n2025-01-28 16:26:03.793 | INFO | tools.llama.generate:generate_long:568 - Bandwidth achieved: 24.34 GB/s\n2025-01-28 16:26:03.793 | INFO | tools.llama.generate:generate_long:573 - GPU Memory used: 2.45 GB\n2025-01-28 16:26:03.793 | INFO | tools.llama.generate:generate_long:509 - Generating sentence 3/4 of sample 1/1\n 0%| | 0/1672 [00:00<?, ?it/s]\n 0%| | 7/1672 [00:00<00:26, 63.08it/s]\n 1%| | 14/1672 [00:00<00:26, 62.91it/s]\n 1%|▏ | 21/1672 [00:00<00:26, 62.97it/s]\n 2%|▏ | 28/1672 [00:00<00:26, 62.73it/s]\n 2%|▏ | 35/1672 [00:00<00:26, 62.46it/s]\n2%|▏ | 39/1672 [00:00<00:26, 61.00it/s]\n2025-01-28 16:26:04.454 | INFO | tools.llama.generate:generate_long:565 - Generated 41 tokens in 0.66 seconds, 62.06 tokens/sec\n2025-01-28 16:26:04.454 | INFO | tools.llama.generate:generate_long:568 - Bandwidth achieved: 24.21 GB/s\n2025-01-28 16:26:04.454 | INFO | tools.llama.generate:generate_long:573 - GPU Memory used: 2.45 GB\n2025-01-28 16:26:04.454 | INFO | tools.llama.generate:generate_long:509 - Generating sentence 4/4 of sample 1/1\n 0%| | 0/1608 [00:00<?, ?it/s]\n 0%| | 7/1608 [00:00<00:25, 63.11it/s]\n 1%| | 14/1608 [00:00<00:25, 63.00it/s]\n1%| | 14/1608 [00:00<00:27, 58.74it/s]\n2025-01-28 16:26:04.709 | INFO | tools.llama.generate:generate_long:565 - Generated 16 tokens in 0.25 seconds, 62.81 tokens/sec\n2025-01-28 16:26:04.709 | INFO | tools.llama.generate:generate_long:568 - Bandwidth achieved: 24.51 GB/s\n2025-01-28 16:26:04.710 | INFO | tools.llama.generate:generate_long:573 - GPU Memory used: 2.45 GB\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/nn/modules/conv.py:306: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.)\nreturn F.conv1d(input, weight, bias, self.stride,\nNext sample", "metrics": { "predict_time": 3.097940238, "total_time": 83.627677 }, "output": "https://replicate.delivery/xezq/I77Wgm5GPZJcPBiGe9WeRYHDfLr5blb16hWlvxnkk3f3xtmQB/generated.wav", "started_at": "2025-01-28T16:26:01.936737Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-kkjxzcufksibrwqp56dqg3nxd4bsxbkgeiscttvpaqnc4nagf4wa", "get": "https://api.replicate.com/v1/predictions/fgdgr9djqxrme0cmnpx9bhp1em", "cancel": "https://api.replicate.com/v1/predictions/fgdgr9djqxrme0cmnpx9bhp1em/cancel" }, "version": "eba2a3e1e07cf38ac2a528d134fdac1cab4d222b8850ac98517635ddf5c1ca75" }Generated in2025-01-28 16:26:02.222 | INFO | tools.llama.generate:generate_long:491 - Encoded text: With tenure, Suzie'd have all 2025-01-28 16:26:02.222 | INFO | tools.llama.generate:generate_long:491 - Encoded text: the more leisure for yachting, 2025-01-28 16:26:02.222 | INFO | tools.llama.generate:generate_long:491 - Encoded text: but her publications are no 2025-01-28 16:26:02.222 | INFO | tools.llama.generate:generate_long:491 - Encoded text: good. 2025-01-28 16:26:02.223 | INFO | tools.llama.generate:generate_long:509 - Generating sentence 1/4 of sample 1/1 0%| | 0/1858 [00:00<?, ?it/s]/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/backends/cuda/__init__.py:342: FutureWarning: torch.backends.cuda.sdp_kernel() is deprecated. In the future, this context manager will be removed. Please see, torch.nn.attention.sdpa_kernel() for the new context manager, with updated signature. warnings.warn( 0%| | 6/1858 [00:00<00:31, 59.00it/s] 1%| | 12/1858 [00:00<00:32, 57.47it/s] 1%| | 19/1858 [00:00<00:30, 60.07it/s] 1%|▏ | 26/1858 [00:00<00:29, 61.43it/s] 2%|▏ | 33/1858 [00:00<00:29, 62.05it/s] 2%|▏ | 40/1858 [00:00<00:29, 62.57it/s] 3%|▎ | 47/1858 [00:00<00:29, 62.38it/s] 3%|▎ | 49/1858 [00:00<00:29, 60.40it/s] 2025-01-28 16:26:03.118 | INFO | tools.llama.generate:generate_long:565 - Generated 51 tokens in 0.90 seconds, 56.95 tokens/sec 2025-01-28 16:26:03.118 | INFO | tools.llama.generate:generate_long:568 - Bandwidth achieved: 22.22 GB/s 2025-01-28 16:26:03.118 | INFO | tools.llama.generate:generate_long:573 - GPU Memory used: 2.45 GB 2025-01-28 16:26:03.119 | INFO | tools.llama.generate:generate_long:509 - Generating sentence 2/4 of sample 1/1 0%| | 0/1759 [00:00<?, ?it/s] 0%| | 7/1759 [00:00<00:27, 62.93it/s] 1%| | 14/1759 [00:00<00:27, 62.96it/s] 1%| | 21/1759 [00:00<00:27, 62.82it/s] 2%|▏ | 28/1759 [00:00<00:28, 61.75it/s] 2%|▏ | 35/1759 [00:00<00:27, 62.10it/s] 2%|▏ | 40/1759 [00:00<00:28, 60.85it/s] 2025-01-28 16:26:03.792 | INFO | tools.llama.generate:generate_long:565 - Generated 42 tokens in 0.67 seconds, 62.37 tokens/sec 2025-01-28 16:26:03.793 | INFO | tools.llama.generate:generate_long:568 - Bandwidth achieved: 24.34 GB/s 2025-01-28 16:26:03.793 | INFO | tools.llama.generate:generate_long:573 - GPU Memory used: 2.45 GB 2025-01-28 16:26:03.793 | INFO | tools.llama.generate:generate_long:509 - Generating sentence 3/4 of sample 1/1 0%| | 0/1672 [00:00<?, ?it/s] 0%| | 7/1672 [00:00<00:26, 63.08it/s] 1%| | 14/1672 [00:00<00:26, 62.91it/s] 1%|▏ | 21/1672 [00:00<00:26, 62.97it/s] 2%|▏ | 28/1672 [00:00<00:26, 62.73it/s] 2%|▏ | 35/1672 [00:00<00:26, 62.46it/s] 2%|▏ | 39/1672 [00:00<00:26, 61.00it/s] 2025-01-28 16:26:04.454 | INFO | tools.llama.generate:generate_long:565 - Generated 41 tokens in 0.66 seconds, 62.06 tokens/sec 2025-01-28 16:26:04.454 | INFO | tools.llama.generate:generate_long:568 - Bandwidth achieved: 24.21 GB/s 2025-01-28 16:26:04.454 | INFO | tools.llama.generate:generate_long:573 - GPU Memory used: 2.45 GB 2025-01-28 16:26:04.454 | INFO | tools.llama.generate:generate_long:509 - Generating sentence 4/4 of sample 1/1 0%| | 0/1608 [00:00<?, ?it/s] 0%| | 7/1608 [00:00<00:25, 63.11it/s] 1%| | 14/1608 [00:00<00:25, 63.00it/s] 1%| | 14/1608 [00:00<00:27, 58.74it/s] 2025-01-28 16:26:04.709 | INFO | tools.llama.generate:generate_long:565 - Generated 16 tokens in 0.25 seconds, 62.81 tokens/sec 2025-01-28 16:26:04.709 | INFO | tools.llama.generate:generate_long:568 - Bandwidth achieved: 24.51 GB/s 2025-01-28 16:26:04.710 | INFO | tools.llama.generate:generate_long:573 - GPU Memory used: 2.45 GB /root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/nn/modules/conv.py:306: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.) return F.conv1d(input, weight, bias, self.stride, Next sample
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