Wire the hosted HiDream I1 int8/fp8 checkpoints
Gate-validated: all 28 per-case pairs pass per scheme (LPIPS suite means 0.291 int8 / 0.278 fp8, in the 50-step trajectory-divergence band; CLIP delta means 0.007-0.008), and the int8 checkpoint is verified bit-identical to on-the-fly quantize across all 1615 state dict tensors (1073 quantized, max abs diff 0.0). Uploaded to unsloth/HiDream-I1-Full-FP8.
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@ -363,6 +363,13 @@ _FAMILIES: tuple[DiffusionFamily, ...] = (
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# need the same TE4 assembly for tiny demand, so no GGUF artifact is wired yet.
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DiffusionFamily(
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name = "hidream-i1",
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# Hosted checkpoints: 28/28 per-case gate pairs per scheme (LPIPS suite means 0.291
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# int8 / 0.278 fp8, the 50-step trajectory band); int8 verified bit-identical to
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# on-the-fly quantize across all 1615 state dict tensors.
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prequant_repos = (
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("int8", "unsloth/HiDream-I1-Full-FP8"),
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("fp8", "unsloth/HiDream-I1-Full-FP8"),
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),
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pipeline_class = "HiDreamImagePipeline",
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transformer_class = "HiDreamImageTransformer2DModel",
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base_repo = "HiDream-ai/HiDream-I1-Full",
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@ -296,6 +296,16 @@ def test_ideogram4_memory_table_counts_both_dits():
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assert text_encoders_gb > 5.0
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def test_hidream_prequant_wiring():
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# Hosted int8/fp8 checkpoints (28/28 per-case gate pairs per scheme; int8 verified
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# bit-identical to on-the-fly quantize) serve the family default base.
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from core.inference.diffusion_families import family_prequant_repo
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fam = detect_family("HiDream-ai/HiDream-I1-Full")
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for scheme in ("int8", "fp8"):
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assert family_prequant_repo(fam, scheme) == "unsloth/HiDream-I1-Full-FP8"
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def test_hidream_quant_schemes_not_denied_and_no_extra_excludes():
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# Measured on a B200 (outputs/hidream_smoke): int8 and fp8 both engage and render
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# cleanly, including a 2-3 token prompt on int8 -- the routed MoE expert Linears
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