fix(model): load transformer from all-in-one checkpoints in native loader

All-in-one exports bundle the text encoder and VAE alongside the
transformer under LDM-style family prefixes (cond_stage_model.,
first_stage_model., text_encoders., vae.). The native loader treated
those keys as a mixed-prefix error and rejected the file. Drop known
companion families before prefix detection and log what was skipped;
keys matching neither a transformer prefix nor a known family still
raise. TE and VAE keep coming from the base repo or their own overrides.

pipelines/native_transformer.py

@@ -19,15 +19,19 @@ from diffusers' ``SINGLE_FILE_LOADABLE_CLASSES`` table.
 Algorithm:
 
 1. Read the safetensors state dict (.gguf and .pth are rejected up front).
-2. Detect and strip one of the spec's known prefixes (raises on mixed prefixes).
-3. Check forbidden markers (catches structural mismatches like Cosmos 1.0 keys
+2. Drop keys belonging to known companion component families (all-in-one
+   exports bundle the text encoder and VAE under prefixes like
+   ``cond_stage_model.`` / ``first_stage_model.``; sdnext sources those
+   components elsewhere).
+3. Detect and strip one of the spec's known prefixes (raises on mixed prefixes).
+4. Check forbidden markers (catches structural mismatches like Cosmos 1.0 keys
    in a Cosmos 2.0 loader).
-4. Partition off sibling component keys (e.g. Anima's bundled ``llm_adapter.*``).
-5. Run the spec's converter if present (else pass through unchanged).
-6. Fetch ``<subfolder>/config.json`` from the base repo, instantiate via
+5. Partition off sibling component keys (e.g. Anima's bundled ``llm_adapter.*``).
+6. Run the spec's converter if present (else pass through unchanged).
+7. Fetch ``<subfolder>/config.json`` from the base repo, instantiate via
    ``cls.from_config``, ``load_state_dict(strict=False)``, validate, dtype-cast,
    quantize, and offload-place.
-7. Repeat the build for each populated sibling (no converter, no quant by
+8. Repeat the build for each populated sibling (no converter, no quant by
    default; sibling weights are read raw from the bundled file).
 
 Returns ``(transformer, sibling_components_dict)``. The dict is empty for
@@ -58,6 +62,13 @@ DEFAULT_ACCEPTABLE_MISSING: tuple[str, ...] = (
     "pos_embedder.",
     "learnable_pos_embed.",
 )
+DEFAULT_IGNORED_PREFIXES: tuple[str, ...] = (
+    "cond_stage_model.",
+    "conditioner.",
+    "first_stage_model.",
+    "text_encoders.",
+    "vae.",
+)
 
 
 class OverrideArchMismatch(Exception):
@@ -106,11 +117,17 @@ class TransformerSpec:
     ``acceptable_missing`` (buffer-only keys left at their init), these are
     zero-filled on load so the branch stays a no-op, matching a base model
     that ships the branch dormant (output projection all-zeros).
+
+    ``ignored_prefixes`` names companion component families (text encoder,
+    VAE) that all-in-one exports bundle alongside the transformer; their keys
+    are dropped before prefix detection rather than treated as a malformed
+    file.
     """
 
     cls: type
     subfolder: str = "transformer"
     prefixes: tuple[str, ...] = DEFAULT_PREFIXES
+    ignored_prefixes: tuple[str, ...] = DEFAULT_IGNORED_PREFIXES
     converter: Callable[[dict], dict] | None = None
     siblings: dict[str, SiblingSpec] = field(default_factory=dict)
     acceptable_missing: tuple[str, ...] = DEFAULT_ACCEPTABLE_MISSING
@@ -246,6 +263,7 @@ def load(
         quant_type = model_quant.get_quant_type(quant_args)
 
     state_dict = sd_models.read_state_dict(local_file, what="transformer")
+    state_dict = drop_companion_keys(state_dict, spec.ignored_prefixes, spec.cls.__name__)
     state_dict, detected_prefix = strip_prefix(state_dict, spec.prefixes, spec.cls.__name__)
     check_forbidden_markers(state_dict, spec.forbidden_markers, spec.cls.__name__, local_file)
     transformer_sd, sibling_sds = partition_siblings(state_dict, spec.siblings)
@@ -309,6 +327,40 @@ def load(
     return transformer, loaded_siblings
 
 
+def drop_companion_keys(state_dict: dict, ignored_prefixes: tuple[str, ...], type_name: str) -> dict:
+    """Remove keys belonging to known non-transformer component families.
+
+    All-in-one exports bundle the text encoder and VAE alongside the
+    transformer under LDM/ComfyUI-style family prefixes (``cond_stage_model.``,
+    ``first_stage_model.``, ``text_encoders.``, ``vae.``). Only the transformer
+    (plus any spec-declared inline siblings) is wanted here; sdnext sources the
+    other components from the base repo or their own override dropdowns.
+    Dropped families are logged so the skip is visible in the load log.
+
+    Raises ValueError when nothing remains after filtering, meaning the
+    selected file holds no transformer at all.
+    """
+    if not ignored_prefixes:
+        return state_dict
+    dropped: dict[str, int] = {}
+    kept: dict = {}
+    for key, value in state_dict.items():
+        prefix = next((p for p in ignored_prefixes if key.startswith(p)), None)
+        if prefix is None:
+            kept[key] = value
+        else:
+            dropped[prefix] = dropped.get(prefix, 0) + 1
+    if not dropped:
+        return state_dict
+    counts = " ".join(f"{prefix.rstrip('.')}={count}" for prefix, count in dropped.items())
+    if not kept:
+        raise ValueError(
+            f"Load model: type={type_name} native_transformer has no transformer keys ({counts})"
+        )
+    log.info(f"Load model: type={type_name} native_transformer skipping bundled components: {counts}")
+    return kept
+
+
 def strip_prefix(state_dict: dict, prefixes: tuple[str, ...], type_name: str) -> tuple[dict, str]:
     """Detect and uniformly strip the most common known prefix from every key.
 

test/test-native-transformer.py

@@ -4,6 +4,7 @@ Offline unit tests for pipelines.native_transformer.
 
 Covers the pure helpers that own per-arch knob handling:
 
+- ``drop_companion_keys`` for filtering bundled TE/VAE families out of all-in-one files
 - ``strip_prefix`` for single/multi prefix detection and mixed-prefix rejection
 - ``partition_siblings`` for inline-sibling key partitioning
 - ``check_forbidden_markers`` for structural-mismatch rejection
@@ -94,6 +95,61 @@ def run_test(cat: str, fn):
         traceback.print_exc()
 
 
+# ============================================================
+# drop_companion_keys
+# ============================================================
+
+def test_drop_companion_keys_no_companions_pass_through():
+    sd = {'net.blocks.0.weight': 1, 'net.blocks.1.weight': 2}
+    out = nt.drop_companion_keys(sd, nt.DEFAULT_IGNORED_PREFIXES, 'Test')
+    assert out == sd, 'files without companion keys must pass through unchanged'
+
+
+def test_drop_companion_keys_filters_all_in_one_layout():
+    sd = {
+        'net.blocks.0.weight': 1,
+        'net.llm_adapter.proj.weight': 2,
+        'cond_stage_model.qwen3_06b.transformer.model.embed_tokens.weight': 3,
+        'first_stage_model.decoder.conv1.weight': 4,
+        'vae.decoder.conv_in.weight': 5,
+        'text_encoders.clip_l.weight': 6,
+    }
+    out = nt.drop_companion_keys(sd, nt.DEFAULT_IGNORED_PREFIXES, 'Test')
+    assert set(out.keys()) == {'net.blocks.0.weight', 'net.llm_adapter.proj.weight'}
+
+
+def test_drop_companion_keys_raises_when_nothing_left():
+    sd = {
+        'cond_stage_model.te.weight': 1,
+        'first_stage_model.decoder.weight': 2,
+    }
+    try:
+        nt.drop_companion_keys(sd, nt.DEFAULT_IGNORED_PREFIXES, 'Test')
+        raise AssertionError('expected ValueError')
+    except ValueError as e:
+        assert 'no transformer keys' in str(e)
+
+
+def test_drop_companion_keys_empty_prefix_tuple_no_op():
+    sd = {'cond_stage_model.te.weight': 1}
+    out = nt.drop_companion_keys(sd, (), 'Test')
+    assert out == sd, 'empty ignored_prefixes must disable filtering'
+
+
+def test_drop_then_strip_all_in_one_layout():
+    """Companion filtering must clear the way for normal prefix detection."""
+    sd = {
+        'net.blocks.0.weight': 1,
+        'net.final_layer.weight': 2,
+        'cond_stage_model.te.weight': 3,
+        'first_stage_model.decoder.weight': 4,
+    }
+    out = nt.drop_companion_keys(sd, nt.DEFAULT_IGNORED_PREFIXES, 'Test')
+    out, prefix = nt.strip_prefix(out, nt.DEFAULT_PREFIXES, 'Test')
+    assert prefix == 'net.'
+    assert set(out.keys()) == {'blocks.0.weight', 'final_layer.weight'}
+
+
 # ============================================================
 # strip_prefix
 # ============================================================
@@ -380,6 +436,7 @@ def test_transformer_spec_defaults():
     assert spec.converter is None
     assert spec.siblings == {}
     assert spec.acceptable_missing == ('rope.', 'pos_embedder.', 'learnable_pos_embed.')
+    assert spec.ignored_prefixes == ('cond_stage_model.', 'conditioner.', 'first_stage_model.', 'text_encoders.', 'vae.')
     assert spec.forbidden_markers == ()
 
 
@@ -779,6 +836,17 @@ def test_load_converter_crash_raises_mismatch():
 # ============================================================
 
 def run_all():
+    log.warning('=== drop_companion_keys ===')
+    cat = category('companion')
+    for fn in [
+        test_drop_companion_keys_no_companions_pass_through,
+        test_drop_companion_keys_filters_all_in_one_layout,
+        test_drop_companion_keys_raises_when_nothing_left,
+        test_drop_companion_keys_empty_prefix_tuple_no_op,
+        test_drop_then_strip_all_in_one_layout,
+    ]:
+        run_test(cat, fn)
+
     log.warning('=== strip_prefix ===')
     cat = category('strip')
     for fn in [