Flux2: support local safetensors paths and stream-load to fix RAM blowup

[deepglugs]

Loading FLUX.2-dev from a custom safetensors file (e.g. a pre-quantized fp8 checkpoint from SwarmUI/ComfyUI) previously failed because the loader assumed a HuggingFace repo id, and even when it worked the full bf16 state_dict was held in RAM alongside the module through the entire quantize pass (assign=True kept the dict and module sharing tensor references), pinning ~24-30GB of bf16 weights while quanto built fp8 QTensors on top — pushing peak host RAM well past 128GB.

Changes in extensions_built_in/diffusion_models/flux2/flux2_model.py:

• name_or_path may now point directly at a .safetensors file. The existing repo-id and directory-of-files paths are unchanged.
• FP8 detection: probe weight dtypes via safe_open and, if pre-quantized fp8 weights are present, auto-enable quantize=True so quanto re-packs into QTensor form and keeps the fp8 memory footprint at runtime.
• Stream-load the transformer one tensor at a time directly into the meta-device module via safe_open + setattr. The full state_dict never exists, so quanto's per-block freeze actually releases the bf16 weights as it goes. Peak RAM during load drops from >128GB to ~55GB on FLUX.2-dev.
• Added flux2_hf_repo_id class attr (default "black-forest-labs/FLUX.2-dev") used as the VAE fallback when name_or_path is a local file so we don't hand a filesystem path to hf_hub_download as a repo id.

Verified end-to-end against a local fp8 FLUX.2-dev checkpoint: detection fires, transformer + Mistral both load and quantize, VAE downloads from the fallback repo, pipe assembles, sample images generate, training proceeds.