Spaces:
Sleeping
Sleeping
| # %% | |
| import time | |
| from IPython.display import Audio | |
| import numpy as np | |
| from scipy.io.wavfile import write | |
| from IPython.display import Audio | |
| import torch | |
| # from transformers import pipeline | |
| from transformers import SeamlessM4Tv2Model | |
| from transformers import AutoProcessor | |
| model_name = "facebook/seamless-m4t-v2-large" | |
| # model_name = "facebook/hf-seamless-m4t-medium" | |
| processor = AutoProcessor.from_pretrained(model_name) | |
| model = SeamlessM4Tv2Model.from_pretrained(model_name) | |
| device = "cuda:0" if torch.cuda.is_available() else "cpu" | |
| # torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32 | |
| model.to(device) | |
| start_time = time.time() | |
| src_lang = "eng" | |
| tgt_lang = "por" | |
| text_to_translate = "My life is a beautifull thing" | |
| text_inputs = processor(text=text_to_translate, | |
| src_lang=src_lang, return_tensors="pt").to(device) | |
| # output_tokens = model.generate( | |
| # **text_inputs, tgt_lang=tgt_lang, generate_speech=False) | |
| # translated_text_from_text = processor.decode( | |
| # output_tokens[0].tolist()[0], skip_special_tokens=True) | |
| # %% | |
| print(text_inputs) | |
| # %% | |
| audio_array_from_text = model.generate( | |
| **text_inputs, tgt_lang=tgt_lang)[0].cpu().numpy().squeeze() | |
| # %% | |
| print(audio_array_from_text) | |
| # %% | |
| a = Audio(audio_array_from_text, rate=model.config.sampling_rate) | |
| print(a) | |
| # %% | |