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970c0d3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | """Model-dependent defaults for the quantization form."""
import logging
import gradio as gr
from src.tools.model_size import get_model_size_b
logger = logging.getLogger(__name__)
def default_quant_method(model, oauth_token: gr.OAuthToken | None = None):
"""Use total parameters (including MoE experts), with Tuning as fallback."""
size = None
if model and model.strip():
try:
size = get_model_size_b(model.strip(), token=oauth_token.token if oauth_token else None)
except Exception:
logger.warning("Could not determine model size for the quantization default")
return gr.update(value=(
"RTN (Round-To-Nearest)" if size is not None and size > 100
else "Tuning (AutoRound, recommended)"
))
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