variant support: WISE_ALPHA, EMB_DIR/OUT_PREFIX

code/hf_jobs/encode_e5_ft.py

@@ -115,6 +115,17 @@ def main():
                                                                  local_dir=f'{WORK}/model')
     log('model files', sorted(os.listdir(mpath)))
     model = SentenceTransformer(mpath, device='cuda', model_kwargs={'torch_dtype': torch.float16})
+    wa = float(os.environ.get('WISE_ALPHA', '0') or 0)
+    if wa > 0:  # WiSE-FT: weights = (1 - a) * stock e5-large + a * this model (fine-tuned), then fp16
+        base = SentenceTransformer('intfloat/multilingual-e5-large', device='cuda', model_kwargs={'torch_dtype': torch.float32})
+        ft32 = SentenceTransformer(mpath, device='cuda', model_kwargs={'torch_dtype': torch.float32})
+        sd_b, sd_f = base.state_dict(), ft32.state_dict()
+        with torch.no_grad():
+            for k, v in base.state_dict().items():
+                if v.is_floating_point():
+                    v.copy_((1 - wa) * sd_b[k] + wa * sd_f[k])
+        model = base.half(); del ft32
+        log(f'WiSE-FT weight average: alpha={wa} (0 = stock e5-large, 1 = {MODEL}@{MODEL_REVISION})')
     model.eval()
     pdt = next(model.parameters()).dtype
     if pdt != torch.float16: