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--- |
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library_name: transformers |
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license: cc |
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datasets: |
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- atlithor/talromur3_without_emotions |
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language: |
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- is |
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base_model: |
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- parler-tts/parler-tts-mini-multilingual-v1.1 |
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pipeline_tag: text-to-speech |
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--- |
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# Model Card for RepeaTTS-level-1 |
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See [Emotive Icelandic](https://huggingface.co/atlithor/EmotiveIcelandic) for more information about this model and the data that it is trained on. |
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The RepeaTTS series is trained on the same data as Emotive Icelandic, but without emotive content disclosure. |
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This model, level-1, corresponds to a model without any further refinement fine-tuning. |
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## Usage |
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Use the code below to get started with the model. |
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```py |
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import torch |
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from parler_tts import ParlerTTSForConditionalGeneration |
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from transformers import AutoTokenizer |
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import soundfile as sf |
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device = "cuda:0" if torch.cuda.is_available() else "cpu" |
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model = ParlerTTSForConditionalGeneration.from_pretrained("atlithor/RepeaTTS-level-1").to(device) |
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tokenizer = AutoTokenizer.from_pretrained("atlithor/EmotiveIcelandic") |
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description_tokenizer = AutoTokenizer.from_pretrained(model.config.text_encoder._name_or_path) |
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prompt = "Þetta er frábær hugmynd!" # E: this is a great idea! |
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description = "The recording is of very high quality, with Ingrid's voice sounding clear and very close up." |
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input_ids = description_tokenizer(description, return_tensors="pt").input_ids.to(device) |
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prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device) |
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generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids) |
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audio_arr = generation.cpu().numpy().squeeze() |
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sf.write("ingrid.wav", audio_arr, model.config.sampling_rate) |
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``` |
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## Citation |
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_coming later_ |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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