Add Qwen3.5-2B text only olive-recipe with INT4 weights and shared INT8 embedding

Qwen-Qwen3.5-2B/baseline/Qwen-Qwen3.5-2B_baseline_mmlu.json

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+{
+    "input_model": {
+        "type": "HfModel",
+        "model_path": "Qwen/Qwen3.5-2B",
+        "load_kwargs": {
+            "torch_dtype": "float16"
+        }
+    },
+    "systems": {
+        "local_system": {
+            "type": "LocalSystem",
+            "accelerators": [
+                {
+                    "device": "gpu",
+                    "execution_providers": ["CUDAExecutionProvider"]
+                }
+            ]
+        }
+    },
+    "evaluators": {
+        "mmlu": {
+            "type": "LMEvaluator",
+            "tasks": ["mmlu"],
+            "model_class": "hf",
+            "batch_size": 8
+        }
+    },
+    "evaluator": "mmlu",
+    "target": "local_system",
+    "log_severity_level": 0,
+    "evaluate_input_model": true
+}

Qwen-Qwen3.5-2B/baseline/requirements.txt

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+accelerate
+datasets
+lm-eval
+torch
+transformers==4.52.4

Qwen-Qwen3.5-2B/cpu/Qwen-Qwen3.5-2B_cpu_int4.json

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+{
+    "input_model": {
+        "type": "HfModel",
+        "model_path": "Qwen/Qwen3.5-2B",
+        "load_kwargs": {
+            "torch_dtype": "float16"
+        }
+    },
+    "systems": {
+        "local_system": {
+            "type": "LocalSystem",
+            "accelerators": [
+                {
+                    "device": "cpu",
+                    "execution_providers": ["CPUExecutionProvider"]
+                }
+            ]
+        }
+    },
+    "passes": {
+        "m": {
+            "type": "ModelBuilder",
+            "precision": "int4",
+            "extra_options": {
+                "exclude_embeds": false
+            }
+        },
+        "q": {
+            "type": "GraphSurgeries",
+            "surgeries": [
+                {"surgeon": "QuantizeEmbeddingInt8"},
+                {"surgeon": "ShareEmbeddingLmHead"}
+            ]
+        }
+    },
+    "target": "local_system",
+    "log_severity_level": 0,
+    "output_dir": "model",
+    "cache_dir": "cache",
+    "no_artifacts": true
+}

Qwen-Qwen3.5-2B/cpu/Qwen-Qwen3.5-2B_cpu_int4_with_eval.json

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+{
+    "input_model": {
+        "type": "HfModel",
+        "model_path": "Qwen/Qwen3.5-2B",
+        "load_kwargs": {
+            "torch_dtype": "float16"
+        }
+    },
+    "systems": {
+        "local_system": {
+            "type": "LocalSystem",
+            "accelerators": [
+                {
+                    "device": "cpu",
+                    "execution_providers": ["CPUExecutionProvider"]
+                }
+            ]
+        }
+    },
+    "passes": {
+        "m": {
+            "type": "ModelBuilder",
+            "precision": "int4",
+            "extra_options": {
+                "exclude_embeds": false
+            }
+        },
+        "q": {
+            "type": "GraphSurgeries",
+            "surgeries": [
+                {"surgeon": "QuantizeEmbeddingInt8"},
+                {"surgeon": "ShareEmbeddingLmHead"}
+            ]
+        }
+    },
+    "evaluators": {
+        "mmlu": {
+            "type": "LMEvaluator",
+            "tasks": ["mmlu"],
+            "batch_size": 8
+        }
+    },
+    "evaluator": "mmlu",
+    "target": "local_system",
+    "log_severity_level": 0,
+    "output_dir": "model",
+    "cache_dir": "cache",
+    "no_artifacts": true
+}

Qwen-Qwen3.5-2B/cpu/README.md

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+# Qwen-Qwen3.5-2B — CPU optimization
+
+This folder contains Olive recipes for optimizing Qwen-Qwen3.5-2B targeting the CPU EP.
+
+## What this folder is for
+
+- Execution Provider: CPU EP
+- Typical precision: INT4 precision by default
+- Example recipe filename: Qwen-Qwen3.5-2B_cpu_int4.json
+
+## Setup
+
+1) Install the main branch of Olive:
+   - pip install git+https://github.com/microsoft/olive.git
+2) Install the appropriate runtime package for this backend:
+   - onnxruntime-genai (CPU build)
+3) Run Olive to build/optimize the model
+   - olive run --config Qwen-Qwen3.5-2B_cpu_int4.json
+
+Additional notes:
+- Pipeline: `SelectiveMixedPrecision` (kld_gradient) → `GPTQ` → `RTN` (8-bit lm_head/embeddings) → `ModelBuilder` → `TieWordEmbeddings`
+- GPTQ group size: 128
+- Uses text-only mode (exclude_embeds=false, prune_lm_head=true) for standalone LLM inference without multimodal pipeline.
+- Runs purely on CPU; no GPU required.
+
+---
+
+This README was auto-generated for the CPU EP of Qwen-Qwen3.5-2B.

Qwen-Qwen3.5-2B/cpu/info.yaml

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+arch: qwen3_5_text
+recipes:
+  - name: Qwen-Qwen3.5-2B_cpu_int4
+    file: Qwen-Qwen3.5-2B_cpu_int4.json
+    devices: cpu
+    eps: CPUExecutionProvider

Qwen-Qwen3.5-2B/cpu/requirements.txt

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+accelerate
+datasets
+onnxruntime-genai
+transformers==4.52.4

Qwen-Qwen3.5-2B/cuda/Qwen-Qwen3.5-2B_cuda_int4.json

@@ -0,0 +1,42 @@
+{
+    "input_model": {
+        "type": "HfModel",
+        "model_path": "Qwen/Qwen3.5-2B",
+        "load_kwargs": {
+            "torch_dtype": "float16"
+        }
+    },
+    "systems": {
+        "local_system": {
+            "type": "LocalSystem",
+            "accelerators": [
+                {
+                    "device": "gpu",
+                    "execution_providers": ["CUDAExecutionProvider"]
+                }
+            ]
+        }
+    },
+    "passes": {
+        "m": {
+            "type": "ModelBuilder",
+            "precision": "int4",
+            "extra_options": {
+                "exclude_embeds": false,
+                "enable_cuda_graph": true
+            }
+        },
+        "q": {
+            "type": "GraphSurgeries",
+            "surgeries": [
+                {"surgeon": "QuantizeEmbeddingInt8"},
+                {"surgeon": "ShareEmbeddingLmHead"}
+            ]
+        }
+    },
+    "target": "local_system",
+    "log_severity_level": 0,
+    "output_dir": "model",
+    "cache_dir": "cache",
+    "no_artifacts": true
+}

Qwen-Qwen3.5-2B/cuda/Qwen-Qwen3.5-2B_cuda_int4_with_eval.json

@@ -0,0 +1,51 @@
+{
+    "input_model": {
+        "type": "HfModel",
+        "model_path": "Qwen/Qwen3.5-2B",
+        "load_kwargs": {
+            "torch_dtype": "float16"
+        }
+    },
+    "systems": {
+        "local_system": {
+            "type": "LocalSystem",
+            "accelerators": [
+                {
+                    "device": "gpu",
+                    "execution_providers": ["CUDAExecutionProvider"]
+                }
+            ]
+        }
+    },
+    "passes": {
+        "m": {
+            "type": "ModelBuilder",
+            "precision": "int4",
+            "extra_options": {
+                "exclude_embeds": false,
+                "enable_cuda_graph": true
+            }
+        },
+        "q": {
+            "type": "GraphSurgeries",
+            "surgeries": [
+                {"surgeon": "QuantizeEmbeddingInt8"},
+                {"surgeon": "ShareEmbeddingLmHead"}
+            ]
+        }
+    },
+    "evaluators": {
+        "mmlu": {
+            "type": "LMEvaluator",
+            "tasks": ["mmlu"],
+            "batch_size": 8
+        }
+    },
+    "evaluator": "mmlu",
+    "target": "local_system",
+    "log_severity_level": 0,
+    "output_dir": "model",
+    "cache_dir": "cache",
+    "no_artifacts": true,
+    "evaluate_input_model": false
+}

Qwen-Qwen3.5-2B/cuda/README.md

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+# Qwen-Qwen3.5-2B — CUDA optimization
+
+This folder contains Olive recipes for optimizing Qwen-Qwen3.5-2B targeting the CUDA EP.
+
+## What this folder is for
+
+- Execution Provider: CUDA EP
+- Typical precision: INT4 precision by default
+- Example recipe filename: Qwen-Qwen3.5-2B_cuda_int4.json
+
+## Setup
+
+1) Install the main branch of Olive:
+   - pip install git+https://github.com/microsoft/olive.git
+2) Install the appropriate runtime package for this backend:
+   - onnxruntime-genai-cuda (CUDA build)
+3) Run Olive to build/optimize the model
+   - olive run --config Qwen-Qwen3.5-2B_cuda_int4.json
+
+Additional notes:
+- Pipeline: `SelectiveMixedPrecision` (kld_gradient) → `GPTQ` → `RTN` (8-bit lm_head/embeddings) → `ModelBuilder` → `TieWordEmbeddings`
+- GPTQ group size: 128
+- Uses text-only mode (exclude_embeds=false, prune_lm_head=true) for standalone LLM inference without multimodal pipeline.
+- Requires NVIDIA GPU with CUDA support.
+- Ensure CUDA toolkit and cuDNN are properly installed.
+
+---
+
+This README was auto-generated for the CUDA EP of Qwen-Qwen3.5-2B.

Qwen-Qwen3.5-2B/cuda/info.yaml

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+arch: qwen3_5_text
+recipes:
+  - name: Qwen-Qwen3.5-2B_cuda_int4
+    file: Qwen-Qwen3.5-2B_cuda_int4.json
+    devices: gpu
+    eps: CUDAExecutionProvider

Qwen-Qwen3.5-2B/cuda/requirements.txt

@@ -0,0 +1,4 @@
+accelerate
+datasets
+onnxruntime-genai
+transformers==4.52.4

Qwen-Qwen3.5-2B/webgpu/Qwen-Qwen3.5-2B_webgpu_int4.json

@@ -0,0 +1,41 @@
+{
+    "input_model": {
+        "type": "HfModel",
+        "model_path": "Qwen/Qwen3.5-2B",
+        "load_kwargs": {
+            "torch_dtype": "float16"
+        }
+    },
+    "systems": {
+        "local_system": {
+            "type": "LocalSystem",
+            "accelerators": [
+                {
+                    "device": "gpu",
+                    "execution_providers": ["WebGpuExecutionProvider"]
+                }
+            ]
+        }
+    },
+    "passes": {
+        "m": {
+            "type": "ModelBuilder",
+            "precision": "int4",
+            "extra_options": {
+                "exclude_embeds": false
+            }
+        },
+        "q": {
+            "type": "GraphSurgeries",
+            "surgeries": [
+                {"surgeon": "QuantizeEmbeddingInt8"},
+                {"surgeon": "ShareEmbeddingLmHead"}
+            ]
+        }
+    },
+    "target": "local_system",
+    "log_severity_level": 0,
+    "output_dir": "model",
+    "cache_dir": "cache",
+    "no_artifacts": true
+}