fixes https://github.com/QuentinFuxa/WhisperLiveKit/issues/269

docs/models_compatible_formats.md

@@ -3,12 +3,14 @@
 The `--model-path` parameter accepts:
 
 ## File Path
-- **`.pt` format only** (required for AlignAtt policy decoder)
+- **`.pt` / `.bin` / `.safetensor` formats** Should be openable by pytorch/safetensor.
 
 ## Directory Path (recommended)
 Must contain:
-- **`.pt` file** (required for decoder)
+- **`.pt` / `.bin` / `.safetensor` file** (required for decoder)
 
 May optionally contain:
 - **`.bin` file** - faster-whisper model for encoder (requires faster-whisper)
-- **`weights.npz`** or **`weights.safetensors`** - for encoder (requires whisper-mlx)
+- **`weights.npz`** or **`weights.safetensors`** - for encoder (requires whisper-mlx)
+
+To improve speed/reduce allucinations, you may want to use `scripts/determine_alignment_heads.py` to determine the alignment heads to use for your model, and use the `--custom-alignment-heads` to pass them to WLK. If not, alignement heads are set to be all the heads of the last half layer of decoder.

whisperlivekit/simul_whisper/backend.py

@@ -41,10 +41,10 @@ def model_path_and_type(model_path):
     
     compatible_whisper_mlx = False
     compatible_faster_whisper = False
-    pt_path = path if path.is_file() and path.suffix.lower() == '.pt' else None
-    if pt_path is None:
-        pt_path = path if path.is_file() and path.suffix.lower() == '.bin' else None
-    if path.is_dir():
+    pytorch_path = None
+    if path.is_file() and path.suffix.lower() in ['.pt', '.safetensors', '.bin']:
+        pytorch_path = path
+    elif path.is_dir():
         for file in path.iterdir():
             if file.is_file():
                 if file.name in ['weights.npz', "weights.safetensors"]:
@@ -52,11 +52,13 @@ def model_path_and_type(model_path):
                 elif file.suffix.lower() == '.bin':
                     compatible_faster_whisper = True
                 elif file.suffix.lower() == '.pt':
-                    pt_path = file
-        if pt_path is None:
+                    pytorch_path = file
+                elif file.suffix.lower() == '.safetensors':
+                    pytorch_path = file
+        if pytorch_path is None:
             if (model_path / Path("pytorch_model.bin")).exists():
-                pt_path = model_path / Path("pytorch_model.bin")
-    return pt_path, compatible_whisper_mlx, compatible_faster_whisper
+                pytorch_path = model_path / Path("pytorch_model.bin")
+    return pytorch_path, compatible_whisper_mlx, compatible_faster_whisper
 
 
 class SimulStreamingOnlineProcessor:
@@ -175,10 +177,10 @@ class SimulStreamingASR():
             self.decoder_type = 'greedy' if self.beams == 1 else 'beam'
 
         self.fast_encoder = False
-        self.pt_path, compatible_whisper_mlx, compatible_faster_whisper = None, True, True
+        self.pytorch_path, compatible_whisper_mlx, compatible_faster_whisper = None, True, True
         if self.model_path:
-            self.pt_path, compatible_whisper_mlx, compatible_faster_whisper = model_path_and_type(self.model_path)
-            self.model_name = self.pt_path.stem
+            self.pytorch_path, compatible_whisper_mlx, compatible_faster_whisper = model_path_and_type(self.model_path)
+            self.model_name = self.pytorch_path.stem
             is_multilingual = not self.model_path.endswith(".en")
         elif self.model_size is not None:
             model_mapping = {
@@ -231,9 +233,10 @@ class SimulStreamingASR():
                 if self.model_path and compatible_whisper_mlx:
                     mlx_model = self.model_path
                 else:
-                    mlx_model = mlx_model_mapping[self.model_name]
-                self.mlx_encoder = load_mlx_encoder(path_or_hf_repo=mlx_model)
-                self.fast_encoder = True
+                    mlx_model = mlx_model_mapping.get(self.model_name)
+                if mlx_model:
+                    self.mlx_encoder = load_mlx_encoder(path_or_hf_repo=mlx_model)
+                    self.fast_encoder = True
             elif HAS_FASTER_WHISPER and compatible_faster_whisper:
                 print('Simulstreaming will use Faster Whisper for the encoder.')
                 if self.model_path and compatible_faster_whisper:
@@ -252,7 +255,7 @@ class SimulStreamingASR():
 
     def load_model(self):
         whisper_model = load_model(
-            name=self.pt_path if self.pt_path else self.model_name,
+            name=self.pytorch_path if self.pytorch_path else self.model_name,
             download_root=self.model_path,
             decoder_only=self.fast_encoder,
             custom_alignment_heads=self.custom_alignment_heads

whisperlivekit/simul_whisper/whisper/__init__.py

@@ -8,6 +8,7 @@ from typing import List, Optional, Union, Dict
 
 import torch
 from tqdm import tqdm
+from pathlib import Path
 
 from .audio import load_audio, log_mel_spectrogram, pad_or_trim
 from .decoding import DecodingOptions, DecodingResult, decode, detect_language
@@ -279,10 +280,20 @@ def load_model(
     if custom_alignment_heads:
         alignment_heads = custom_alignment_heads.encode()
 
-    with (
-        io.BytesIO(checkpoint_file) if in_memory else open(checkpoint_file, "rb")
-    ) as fp:
-        checkpoint = torch.load(fp, map_location=device)
+    if isinstance(checkpoint_file, Path) and checkpoint_file.suffix == '.safetensors':
+        try:
+            from safetensors.torch import load_file
+        except ImportError:
+            raise ImportError("Please install safetensors to load .safetensors model files: `pip install safetensors`")
+        if in_memory:
+            checkpoint = load_file(checkpoint_file, device=device)
+        else:
+            checkpoint = load_file(checkpoint_file, device=device)
+    else:
+        with (
+            io.BytesIO(checkpoint_file) if in_memory else open(checkpoint_file, "rb")
+        ) as fp:
+            checkpoint = torch.load(fp, map_location=device)
     del checkpoint_file
 
     dims_cfg = checkpoint.get("dims") if isinstance(checkpoint, dict) else None