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mrq 2024-11-17 09:28:33 -06:00
parent 23fdba0c98
commit a3e1fa3518
2 changed files with 3 additions and 1 deletions
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2
vall_e/models/base.py
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@ -1221,8 +1221,10 @@ class Base(nn.Module):
)
"""
"""
if classifier_level == "AR:0:0":
classifier_level = "NAR:0:0"
"""
embedding = self.resps_emb(
input if input.dim() == 1 or quant_level == 0 else input[:, :quant_level],

2
vall_e/webui.py
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@ -464,7 +464,7 @@ with ui:
with gr.Row():
layout["inference_tts"]["inputs"]["input-prompt-prefix"] = gr.Checkbox(label="Input Prompt as Prefix", info="Treats the input prompt clip as the prefix of the generated sequence.")
layout["inference_tts"]["inputs"]["prefix-silence"] = gr.Slider(value=0.0, minimum=0.0, maximum=1.0, step=0.05, label="Silence Prefix Duration", info="Amount of silence to prefix to the output response before beginning inference.")
layout["inference_tts"]["inputs"]["modality"] = gr.Dropdown(value="AR+NAR", choices=["AR+NAR", "NAR-len"], label="Modality", info="Whether to inference with the AR+NAR or through the NAR-len.")
layout["inference_tts"]["inputs"]["modality"] = gr.Dropdown(value="Auto", choices=["Auto", "AR+NAR", "NAR-len"], label="Modality", info="Whether to inference with the AR+NAR or through the NAR-len.")
with gr.Row():
layout["inference_tts"]["inputs"]["beam-width"] = gr.Slider(value=0, minimum=0, maximum=32, step=1, label="Beam Width", info="Number of branches to search through for beam search sampling.")
layout["inference_tts"]["inputs"]["dynamic-sampling"] = gr.Checkbox(label="Dynamic Temperature", info="Dynamically adjusts the temperature based on the highest confident predicted token per sampling step.")