Delete pixeldit/modeling_pixeldit.py with huggingface_hub

pixeldit/modeling_pixeldit.py

@@ -1,47 +0,0 @@
-"""
-PixelDiT model loader.
-
-Usage:
-    from modeling_pixeldit import load_pixeldit
-    model = load_pixeldit()
-    out = model(x, t, y)   # [B,3,H,W], [B], [B,300,2304] -> [B,3,H,W]
-"""
-
-import sys
-import torch
-
-sys.path.insert(0, "/home/nobus/Raid0/PixelDiT")
-from pixdit_core.pixeldit_t2i import PixDiT_T2I
-
-_CKPT = (
-    "/home/nobus/.cache/huggingface/hub/"
-    "models--nvidia--PixelDiT-1300M-1024px/snapshots/"
-    "7c63b99a7a399918a1d6478b095698a65f664847/pixeldit_t2i_v1.pth"
-)
-
-_ARCH = dict(
-    in_channels=3,
-    num_groups=24,
-    hidden_size=1536,
-    pixel_hidden_size=16,
-    pixel_attn_hidden_size=1152,
-    pixel_num_groups=16,
-    patch_depth=14,
-    pixel_depth=2,
-    patch_size=16,
-    txt_embed_dim=2304,
-    txt_max_length=300,
-)
-
-
-def load_pixeldit(checkpoint=_CKPT, device="cuda", dtype=torch.bfloat16):
-    model = PixDiT_T2I(**_ARCH)
-    state = torch.load(checkpoint, map_location="cpu", weights_only=False)
-    sd = state.get("state_dict", state)
-    sd = {(k[5:] if k.startswith("core.") else k): v for k, v in sd.items()}
-    missing, _ = model.load_state_dict(sd, strict=False)
-    if missing:
-        print(f"[modeling] {len(missing)} missing keys (expected)")
-    model = model.to(device).to(dtype).eval()
-    print(f"[modeling] PixelDiT loaded — {sum(p.numel() for p in model.parameters()):,} params")
-    return model