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Use packaged Qwen tokenizer assets

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This commit is contained in:
Daniel Maddern 2026-08-12 14:39:18 +07:00
parent f90801ea8a
commit 68606e1a30
2 changed files with 3 additions and 2 deletions
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3
src/h3_blackwell_runtime/qwen3vl_text.py
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@ -155,9 +155,10 @@ class Qwen3VL32BTextEncoder(nn.Module):
class Qwen3VLPromptConditioner: class Qwen3VLPromptConditioner:
"""Tokenize raw H3 prompt text and produce Qwen layer-50 conditioning.""" """Tokenize raw H3 prompt text and produce Qwen layer-50 conditioning."""
def __init__(self, checkpoint_path: str | Path, tokenizer_dir: str | Path, *, device: str | torch.device = "cuda", dtype: torch.dtype = torch.bfloat16): def __init__(self, checkpoint_path: str | Path, tokenizer_dir: str | Path | None = None, *, device: str | torch.device = "cuda", dtype: torch.dtype = torch.bfloat16):
from .conditioning import H3PromptTokenizer from .conditioning import H3PromptTokenizer
tokenizer_dir = tokenizer_dir or Path(__file__).with_name("qwen25_tokenizer")
self.tokenizer = H3PromptTokenizer(tokenizer_dir) self.tokenizer = H3PromptTokenizer(tokenizer_dir)
self.encoder = Qwen3VL32BTextEncoder(checkpoint_path, device=device, dtype=dtype) self.encoder = Qwen3VL32BTextEncoder(checkpoint_path, device=device, dtype=dtype)
self.device = device self.device = device

2
tools/compare_fl2va_steps.py
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@ -17,7 +17,7 @@ initial = torch.load(f"{root}/initial.pt", map_location="cuda", weights_only=Fal
steps = [torch.load(path, map_location="cuda", weights_only=False) for path in sorted(glob.glob(f"{root}/step_*.pt"))] steps = [torch.load(path, map_location="cuda", weights_only=False) for path in sorted(glob.glob(f"{root}/step_*.pt"))]
sigmas = initial["sigmas"].to("cuda") sigmas = initial["sigmas"].to("cuda")
checkpoint = H3Checkpoint("/models/minimax_h3_fl2va_pruned_nvfp4.safetensors") checkpoint = H3Checkpoint("/models/minimax_h3_fl2va_pruned_nvfp4.safetensors")
text = H3TokenRefiner(checkpoint)(Qwen3VLPromptConditioner("/text-encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors", "/opt/h3-blackwell-runtime/qwen25_tokenizer")("A brass-and-paper dragon flies above a rain-washed old city at blue hour.")) text = H3TokenRefiner(checkpoint)(Qwen3VLPromptConditioner("/text-encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors")("A brass-and-paper dragon flies above a rain-washed old city at blue hour."))
model = H3PackedDenoiser.from_checkpoint(checkpoint, attention_backend="sage2").eval() model = H3PackedDenoiser.from_checkpoint(checkpoint, attention_backend="sage2").eval()
packer = H3PromptPacker(checkpoint) packer = H3PromptPacker(checkpoint)