feat(mlx-lm): export the GGUF (fp16) format model weights from fuse.py (#555)

* wip

* wip

* feat: convert mlx model to gguf f16

* chore: conver norm layer to float32 to avoid overflow issue

* chore: add support for mixtral

* chore: clean up

* chore: remove unused import statement

* chore: clean up weight name mapping

* version and readme

* actual version bump

---------

Co-authored-by: Awni Hannun <awni@apple.com>

llms/mlx_lm/fuse.py

@@ -3,10 +3,10 @@ import glob
 import json
 import shutil
 from pathlib import Path
-from typing import Any, Dict, Union
 
 from mlx.utils import tree_flatten, tree_unflatten
 
+from .gguf import convert_to_gguf
 from .tuner.lora import LoRALinear
 from .tuner.utils import apply_lora_layers, dequantize
 from .utils import (
@@ -53,6 +53,17 @@ def parse_arguments() -> argparse.Namespace:
         help="Generate a de-quantized model.",
         action="store_true",
     )
+    parser.add_argument(
+        "--export-gguf",
+        help="Export model weights in GGUF format.",
+        action="store_true",
+    )
+    parser.add_argument(
+        "--gguf-path",
+        help="Path to save the exported GGUF format model weights. Default is ggml-model-f16.gguf.",
+        default="ggml-model-f16.gguf",
+        type=str,
+    )
     return parser.parse_args()
 
 
@@ -95,6 +106,14 @@ def main() -> None:
 
     save_config(config, config_path=save_path / "config.json")
 
+    if args.export_gguf:
+        model_type = config["model_type"]
+        if model_type not in ["llama", "mixtral", "mistral"]:
+            raise ValueError(
+                f"Model type {model_type} not supported for GGUF conversion."
+            )
+        convert_to_gguf(model_path, weights, config, str(save_path / args.gguf_path))
+
     if args.upload_repo is not None:
         hf_path = args.hf_path or (
             args.model if not Path(args.model).exists() else None