SP-PE-Qwen3.5-35B-A3B
Structured-Prompt Prompt-Expansion model built on top of Qwen3.5-35B-A3B.
Takes a natural-language prompt (+ target aspect ratio) and emits a
Structured Prompt JSON suitable for a QwenImage-style text-to-image DiT.
Part of the Context-Scaling project.
- Paper: Scaling Properties of Text Conditioning in Visual Generation
- Project page: https://heheyas.github.io/context-scaling/
- Code: https://github.com/heheyas/context-scaling
Usage
Serve via vLLM:
vllm serve heheyas/SP-PE-Qwen3.5-35B-A3B \
--quantization fp8 \
--kv-cache-dtype fp8 \
--language-model-only \
--max-model-len 8192
Or load with transformers (bf16, needs ~70 GB):
from transformers import AutoTokenizer, AutoModelForCausalLM
tok = AutoTokenizer.from_pretrained("heheyas/SP-PE-Qwen3.5-35B-A3B", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
"heheyas/SP-PE-Qwen3.5-35B-A3B",
torch_dtype="bfloat16",
device_map="auto",
trust_remote_code=True,
)
Notes
- 16 safetensors shards, ~66 GB in bf16.
- The
--language-model-onlyflag is used at serving time because we only need the text path for the PE task; the vision tower ships along for compatibility but is not exercised.