mirror of https://github.com/coqui-ai/TTS.git
update docs
parent
5c81500e3e
commit
ea56ec041f
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@ -115,7 +115,7 @@ model.load_checkpoint(config, checkpoint_dir="/path/to/xtts/", use_deepspeed=Tru
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model.cuda()
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print("Computing speaker latents...")
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gpt_cond_latent, diffusion_conditioning, speaker_embedding = model.get_conditioning_latents(audio_path=["reference.wav"])
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gpt_cond_latent, speaker_embedding = model.get_conditioning_latents(audio_path=["reference.wav"])
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print("Inference...")
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out = model.inference(
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@ -123,7 +123,6 @@ out = model.inference(
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"en",
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gpt_cond_latent,
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speaker_embedding,
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diffusion_conditioning,
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temperature=0.7, # Add custom parameters here
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)
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torchaudio.save("xtts.wav", torch.tensor(out["wav"]).unsqueeze(0), 24000)
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@ -152,7 +151,7 @@ model.load_checkpoint(config, checkpoint_dir="/path/to/xtts/", use_deepspeed=Tru
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model.cuda()
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print("Computing speaker latents...")
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gpt_cond_latent, _, speaker_embedding = model.get_conditioning_latents(audio_path=["reference.wav"])
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gpt_cond_latent, speaker_embedding = model.get_conditioning_latents(audio_path=["reference.wav"])
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print("Inference...")
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t0 = time.time()
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@ -209,7 +208,7 @@ model.load_checkpoint(config, checkpoint_path=XTTS_CHECKPOINT, vocab_path=TOKENI
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model.cuda()
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print("Computing speaker latents...")
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gpt_cond_latent, diffusion_conditioning, speaker_embedding = model.get_conditioning_latents(audio_path=[SPEAKER_REFERENCE])
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gpt_cond_latent, speaker_embedding = model.get_conditioning_latents(audio_path=[SPEAKER_REFERENCE])
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print("Inference...")
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out = model.inference(
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@ -217,7 +216,6 @@ out = model.inference(
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"en",
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gpt_cond_latent,
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speaker_embedding,
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diffusion_conditioning,
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temperature=0.7, # Add custom parameters here
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)
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torchaudio.save(OUTPUT_WAV_PATH, torch.tensor(out["wav"]).unsqueeze(0), 24000)
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