Add convert.py.

convert.py

@@ -0,0 +1,26 @@
+from transformers import AutoModelForCausalLM
+import torch
+from safetensors.torch import save_file
+
+model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct", trust_remote_code=True)
+
+params = model.state_dict()
+params2 = {}
+
+for r in params.keys():
+    if "gate_up_proj" in r:
+        (gate, up) = params[r].chunk(2)
+        params2[r.replace("gate_up_proj", "gate_proj")] = gate
+        params2[r.replace("gate_up_proj", "up_proj")] = up
+    elif "qkv_proj" in r:
+        (q, k, v) = params[r].chunk(3)
+        params2[r.replace("qkv_proj", "q_proj")] = q
+        params2[r.replace("qkv_proj", "k_proj")] = k
+        params2[r.replace("qkv_proj", "v_proj")] = v
+    else:
+        params2[r] = params[r]
+
+for r in params2.keys():
+    params2[r] = torch.tensor(params2[r].clone().detach(), dtype=torch.bfloat16)
+
+save_file(params2, "model-00001-of-00001.safetensors", metadata={"format": "pt"})