atlithor
/

RepeaTTS-level-1

@@ -1,176 +1,52 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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@@ -179,21 +55,3 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
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 ---
 library_name: transformers
+license: cc
+datasets:
+- atlithor/talromur3_without_emotions
+language:
+- is
+base_model:
+- parler-tts/parler-tts-mini-multilingual-v1.1
+pipeline_tag: text-to-speech
 ---
+# Model Card for RepeaTTS-level-1
+See [Emotive Icelandic](https://huggingface.co/atlithor/EmotiveIcelandic) for more information about this model and the data that it is trained on.
+The RepeaTTS series is trained on the same data as Emotive Icelandic, but without emotive content disclosure.
+This model, level-1, corresponds to a model without any further refinement fine-tuning.
+## Usage
 Use the code below to get started with the model.
+```py
+import torch
+from parler_tts import ParlerTTSForConditionalGeneration
+from transformers import AutoTokenizer
+import soundfile as sf
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+model = ParlerTTSForConditionalGeneration.from_pretrained("atlithor/RepeaTTS-level-1").to(device)
+tokenizer = AutoTokenizer.from_pretrained("atlithor/EmotiveIcelandic")
+description_tokenizer = AutoTokenizer.from_pretrained(model.config.text_encoder._name_or_path)
+prompt = "Þetta er frábær hugmynd!" # E: this is a great idea!
+description = "The recording is of very high quality, with Ingrid's voice sounding clear and very close up."
+input_ids = description_tokenizer(description, return_tensors="pt").input_ids.to(device)
+prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
+generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
+audio_arr = generation.cpu().numpy().squeeze()
+sf.write("ingrid.wav", audio_arr, model.config.sampling_rate)
+```
+## Citation
+_coming later_
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