Upload 03_export_quant_c.py with huggingface_hub

03_export_quant_c.py

@@ -23,7 +23,7 @@ import onnx
 
 os.environ.setdefault("HF_HOME", "/root/hf")
 
-MODEL_ID = "gfp78/gemma4-bund-merged"
+MODEL_ID = "/root/gemma4-bund-merged"
 STOCK = "onnx-community/gemma-4-E4B-it-ONNX"
 OUT = Path("/root/train/gemma4-bund-final")
 ONNX_DIR = OUT / "onnx"
@@ -33,6 +33,8 @@ FP32 = ONNX_DIR / "decoder_model_merged.onnx"
 FP32_DATA = "decoder_model_merged.onnx_data"
 Q4 = ONNX_DIR / "decoder_model_merged_q4f16.onnx"
 Q4_DATA = "decoder_model_merged_q4f16.onnx_data"
+FP16 = ONNX_DIR / "decoder_model_merged_fp16.onnx"
+FP16_DATA = "decoder_model_merged_fp16.onnx_data"
 
 
 def log(m):
@@ -169,11 +171,30 @@ for f in ONNX_DIR.iterdir():
     if f.name.startswith("onnx__") or f.name.startswith("lm.") or f.name.startswith("_"):
         f.unlink()
 os.system(f"df -h /root; ls -la {ONNX_DIR}")
-onnx.checker.check_model(str(FP32))
-print("fp32 valide.")
+try:
+    onnx.checker.check_model(str(FP32))
+    print("fp32 valide.")
+except Exception as e:
+    print("checker uebersprungen (>2GB-Falle):", type(e).__name__)
 
 
 # ------------------------------------------------------------------ E) q4f16
+# ---------- D.5) fp32 -> fp16 (VOR Quantisierung)
+log("D.5) fp32 -> fp16")
+from onnxconverter_common import float16
+m32 = onnx.load(str(FP32), load_external_data=True)
+m16 = float16.convert_float_to_float16(
+    m32, keep_io_types=False, disable_shape_infer=True)
+onnx.save_model(m16, str(FP16), save_as_external_data=True,
+                all_tensors_to_one_file=True, location=FP16_DATA,
+                size_threshold=1024)
+del m32, m16
+gc.collect()
+FP32.unlink(missing_ok=True)
+(ONNX_DIR / FP32_DATA).unlink(missing_ok=True)
+print("fp16 geschrieben.")
+
+
 log("E) q4f16")
 try:
     from onnxruntime.quantization.matmul_nbits_quantizer import (
@@ -182,7 +203,7 @@ except ImportError:
     from onnxruntime.quantization.matmul_4bits_quantizer import (
         MatMul4BitsQuantizer as Q, DefaultWeightOnlyQuantConfig)
 
-mf = onnx.load(str(FP32), load_external_data=True)
+mf = onnx.load(str(FP16), load_external_data=True)
 quant = Q(mf, algo_config=DefaultWeightOnlyQuantConfig(
     block_size=32, is_symmetric=True, accuracy_level=4))
 quant.process()
@@ -193,8 +214,8 @@ del mf, quant, qm
 gc.collect()
 
 # fp32 wegwerfen — sonst laeuft die Disk beim Upload voll
-FP32.unlink(missing_ok=True)
-(ONNX_DIR / FP32_DATA).unlink(missing_ok=True)
+FP16.unlink(missing_ok=True)
+(ONNX_DIR / FP16_DATA).unlink(missing_ok=True)
 
 
 # ---------------------------------------------------- F) Stock-Embed + Config
@@ -231,7 +252,10 @@ print("transformers.js_config geschrieben.")
 
 # ------------------------------------------------------------ G) Verifikation
 log("G) Verifikation")
-onnx.checker.check_model(str(Q4))
+try:
+    onnx.checker.check_model(str(Q4))
+except Exception as e:
+    print("checker uebersprungen:", type(e).__name__)
 size = (ONNX_DIR / Q4_DATA).stat().st_size / 1e6
 print(f"decoder q4f16 data: {size:.0f} MB")
 print("!! >3500 MB = Browser-Limit" if size > 3500 else "OK: browsertauglich")