update doc

Author: Qubitium

README.md

@@ -33,24 +33,38 @@ from defuser import convert_model, replace_fused_blocks
 ```
 
 - `replace_fused_blocks(model_type)` patches supported HF model classes before `from_pretrained()` or direct model construction.
-- `convert_model(model, cleanup_original=True, max_layers=None)` converts an already loaded model in place. This is the runtime defusion path used for `qwen3_5_moe` style checkpoints.
+- `convert_model(model, cleanup_original=True, max_layers=None)` converts an already loaded model in place. This is the runtime defusion path for supported post-load expert and MLP conversions, including `qwen3_5_moe` style checkpoints.
 - Defuser is designed and CI-tested for `transformers>=5.3.0`, and support is only offered for that version range. Older versions log a warning on these public APIs and are skipped as unsupported.
 
 ## Supported Models
 
-| Model type | Recommended entrypoint | Defused op performed |
+Defuser currently supports the following `transformers==5.3.0` `model_type` values.
+
+### `replace_fused_blocks(model_type)` before load
+
+| Model type | Defused op performed |
+| --- | --- |
+| `glm4_moe` | Replaces `Glm4MoeMoE` with a defused per-expert linear MoE block. |
+| `glm4v` | Replaces the fused text MLP with split `gate_proj`, `up_proj`, and `down_proj` layers. Also splits fused checkpoint `mlp.gate_up_proj.weight` into `mlp.gate_proj.weight` + `mlp.up_proj.weight`. |
+| `mixtral` | Replaces `MixtralSparseMoeBlock` with `LinearMixtralSparseMoeBlock`. Also remaps legacy Mixtral checkpoint keys and splits fused expert `gate_up_proj` tensors into per-expert `gate_proj` and `up_proj`, plus per-expert `down_proj`. |
+| `qwen2_moe` | Replaces `Qwen2MoeSparseMoeBlock` with a defused per-expert linear MoE block. |
+| `qwen3_moe` | Replaces `Qwen3MoeSparseMoeBlock` with a defused per-expert linear MoE block. |
+| `qwen3_next` | Replaces `Qwen3NextSparseMoeBlock` with a defused per-expert linear MoE block. |
+| `qwen3_omni_moe` | Replaces both thinker and talker text sparse MoE blocks with defused per-expert linear blocks and applies small runtime compatibility patches for text `forward()` and `generate()`. |
+
+### `convert_model(model)` after load
+
+| Pattern | Supported model types | Defused op performed |
 | --- | --- | --- |
-| `mixtral` | `replace_fused_blocks("mixtral")` before load | Replaces `MixtralSparseMoeBlock` with `LinearMixtralSparseMoeBlock`. Also remaps legacy Mixtral checkpoint keys and splits fused expert `gate_up_proj` tensors into per-expert `gate_proj` and `up_proj`, plus per-expert `down_proj`. |
-| `qwen2_moe` | `replace_fused_blocks("qwen2_moe")` before load | Replaces `Qwen2MoeSparseMoeBlock` with a defused per-expert linear MoE block. |
-| `qwen3_moe` | `replace_fused_blocks("qwen3_moe")` before load | Replaces `Qwen3MoeSparseMoeBlock` with a defused per-expert linear MoE block. |
-| `qwen3_5_moe` | `convert_model(model)` after load | Runtime expert tensor defusion. Splits fused `gate_up_proj` into `gate_proj` + `up_proj` and converts 3D expert tensors into numbered expert `nn.Linear` modules. |
-| `qwen3_5_moe_text` | `convert_model(model)` after load | Same runtime expert tensor defusion path as `qwen3_5_moe`, applied to the text-only backbone. |
-| `qwen3_next` | `replace_fused_blocks("qwen3_next")` before load | Replaces `Qwen3NextSparseMoeBlock` with a defused per-expert linear MoE block. |
-| `qwen3_omni_moe` | `replace_fused_blocks("qwen3_omni_moe")` before load | Replaces the thinker text sparse MoE block with a defused per-expert linear block and applies small runtime compatibility patches for text `forward()` and `generate()`. |
-| `glm4_moe` | `replace_fused_blocks("glm4_moe")` before load | Replaces `Glm4MoeMoE` with a defused per-expert linear MoE block. |
-| `glm4v` | `replace_fused_blocks("glm4v")` before load | Replaces the fused text MLP with split `gate_proj`, `up_proj`, and `down_proj` layers. Also splits fused checkpoint `mlp.gate_up_proj.weight` into `mlp.gate_proj.weight` + `mlp.up_proj.weight`. |
-| `gpt_oss` | `convert_model(model)` after load | Runtime expert tensor defusion. Splits fused transposed expert `gate_up_proj` into per-expert `gate_proj` + `up_proj`, carries over expert biases, and converts fused expert tensors into numbered expert `nn.Linear` modules. |
-| `llama4` | `convert_model(model)` after load | Runtime expert tensor defusion. Splits fused transposed expert `gate_up_proj` into per-expert `gate_proj` + `up_proj`, converts fused expert tensors into numbered expert `nn.Linear` modules, and preserves the llama4 batched expert-input execution contract. |
+| Standard routed expert tensors | `deepseek_v2`, `dots1`, `ernie4_5_moe`, `ernie4_5_vl_moe`, `exaone_moe`, `flex_olmo`, `glm4_moe_lite`, `glm4v_moe`, `hunyuan_v1_moe`, `jamba`, `lfm2_moe`, `minimax`, `minimax_m2`, `olmoe`, `qwen3_vl_moe`, `solar_open` | Splits fused expert tensors into numbered expert `nn.Linear` modules with per-expert `gate_proj`, `up_proj`, and `down_proj`. |
+| Mixed sparse and shared experts | `deepseek_v3`, `glm_moe_dsa`, `qwen3_5_moe`, `qwen3_5_moe_text` | Runtime expert tensor defusion for routed experts while preserving the model's shared-expert path. |
+| Transposed or packed expert tensors | `gpt_oss`, `phimoe` | Splits transposed fused expert `gate_up_proj` tensors into per-expert `gate_proj` + `up_proj`, preserves expert bias when present, and converts expert tensors into numbered expert `nn.Linear` modules. |
+| Flattened expert layout | `dbrx` | Rebuilds the flattened DBRX expert FFN weights into numbered expert `gate_proj`, `up_proj`, and `down_proj` `nn.Linear` modules. |
+| Batched expert-input execution | `llama4` | Runtime expert tensor defusion plus preservation of the llama4 batched expert-input execution contract. |
+| Non-gated expert MLPs | `nemotron_h` | Converts routed expert tensors into numbered `up_proj` and `down_proj` `nn.Linear` modules for non-gated experts. |
+| Parallel expert blocks | `granitemoe`, `granitemoehybrid`, `granitemoeshared`, `jetmoe` | Converts packed expert weight tensors into numbered expert `linear` modules while keeping grouped expert execution intact. |
+| Routed experts with identity experts | `longcat_flash` | Defuses routed experts into numbered `gate_proj`, `up_proj`, and `down_proj` modules and preserves zero or identity experts. |
+| Fused dense `gate_up_proj` MLPs | `dia`, `glm`, `glm4`, `glm_image`, `glm_ocr`, `phi3`, `phi4_multimodal`, `zamba2` | Splits fused dense `gate_up_proj` layers into `gate_proj` + `up_proj` and updates the block `forward()` to preserve the original MLP math. |
 
 ## Workflow Summary