v1.3.2

[v1.3.2] 2026-08-24

Bug Fix

• Fix WikiText dataset loading in clean environments by using the canonical
  Salesforce/wikitext dataset ID for perplexity evaluation and LoRA SFT examples.
• Fix warning regarding the data type arguments of Transformers.
• Fixed GemLite AssertionError during CPU inference execution for OneComp with Llama.cpp.
• Fixed QuantizedModelLoader.load_quantized_model() calling unfuse_moe_experts() twice on non-fused MoE checkpoints. An earlier unconditional unfuse (run right after building the empty model) was left in place when the checkpoint-aware unfuse (added for gpt-oss fused-MoE support) was introduced. The redundant unconditional call was removed, and the checkpoint-aware unfuse now runs before _remap_state_dict_keys() so key remapping still aligns against the unfused per-expert module paths. This also prevents wrongly unfusing gpt-oss fused-MoE checkpoints, whose fused 3D expert tensors must be loaded as-is (quantized_model_loader.py).

Documentation

• Add troubleshooting information for running OneComp with Llama.cpp on macOS.