actually ar temp 0.5 with rep pen 1.125 seems to have the benefits of better outputs without it degrading some of the time but not all the time

This commit is contained in:
mrq 2024-10-23 00:03:35 -05:00
parent 8920e5e86b
commit 92e6bff6dc
3 changed files with 4 additions and 4 deletions

View File

@ -21,7 +21,7 @@ def main():
parser.add_argument("--max-ar-steps", type=int, default=12 * cfg.dataset.frames_per_second)
parser.add_argument("--max-nar-levels", type=int, default=7)
parser.add_argument("--ar-temp", type=float, default=0.0)
parser.add_argument("--ar-temp", type=float, default=0.5)
parser.add_argument("--nar-temp", type=float, default=0.0)
parser.add_argument("--min-ar-temp", type=float, default=-1.0)
parser.add_argument("--min-nar-temp", type=float, default=-1.0)

View File

@ -368,7 +368,7 @@ class AR_NAR(Base):
mirostat = sampled.scores
elif sampling_beam_width > 0:
# expand tuple
scores = sampled.scores
s = sampled.scores
# first step, expand batch
if batch_size == 1:
batch_size = sampling_beam_width
@ -379,7 +379,7 @@ class AR_NAR(Base):
start_slice = start_slice * sampling_beam_width
stopped = torch.zeros(batch_size, device=device).bool()
scores = [ scores[i] + score for i, score in enumerate(scores) ]
scores = [ scores[i] + score for i, score in enumerate(s) ]
# append tokens
for i, ri in enumerate(r):

View File

@ -351,7 +351,7 @@ with ui:
layout["inference_tts"]["inputs"]["max-nar-levels"] = gr.Slider(value=7, minimum=0, maximum=7, step=1, label="Max NAR Levels", info="Limits how many steps to perform in the NAR pass.")
layout["inference_tts"]["inputs"]["input-prompt-length"] = gr.Slider(value=5.0, minimum=0.0, maximum=12.0, step=0.05, label="Input Prompt Repeat/Trim Length", info="Repeats and trims the input prompt down to X seconds. Set 0 to disable.")
with gr.Row():
layout["inference_tts"]["inputs"]["ar-temp"] = gr.Slider(value=0.0, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (AR)", info="Modifies the randomness from the samples in the AR. (0 to greedy* sample)")
layout["inference_tts"]["inputs"]["ar-temp"] = gr.Slider(value=0.5, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (AR)", info="Modifies the randomness from the samples in the AR. (0 to greedy* sample)")
layout["inference_tts"]["inputs"]["nar-temp"] = gr.Slider(value=0.0, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (NAR)", info="Modifies the randomness from the samples in the NAR. (0 to greedy sample)")
with gr.Row():
if cfg.experimental: