Merge pull request #20 from MoonshotAI/fix-bug-cannot-load-from-model-id

Fix bug： cannot load from model-id

kimia_infer/api/kimia.py

@@ -9,13 +9,23 @@ from transformers import AutoModelForCausalLM
 from kimia_infer.models.detokenizer import get_audio_detokenizer
 from .prompt_manager import KimiAPromptManager
 from kimia_infer.utils.sampler import KimiASampler
-
+from huggingface_hub import snapshot_download
 
 class KimiAudio(object):
     def __init__(self, model_path: str, load_detokenizer: bool = True):
         logger.info(f"Loading kimi-audio main model")
+
+        if os.path.exists(model_path):
+            # local path
+            cache_path = model_path
+        else:
+            # cache everything if model_path is a model-id
+            cache_path = snapshot_download(model_path)
+    
+        logger.info(f"Looking for resources in {cache_path}")
+        logger.info(f"Loading whisper model")
         self.alm = AutoModelForCausalLM.from_pretrained(
-            model_path, torch_dtype=torch.bfloat16, trust_remote_code=True
+            cache_path, torch_dtype=torch.bfloat16, trust_remote_code=True
         )
         self.alm = self.alm.to(torch.cuda.current_device())
 
@@ -23,18 +33,9 @@ class KimiAudio(object):
         self.kimia_token_offset = model_config.kimia_token_offset
 
         self.prompt_manager = KimiAPromptManager(
-            model_path=model_path, kimia_token_offset=self.kimia_token_offset
+            model_path=cache_path, kimia_token_offset=self.kimia_token_offset
         )
 
-        if os.path.exists(model_path):
-            # local path
-            cache_path = model_path
-        else:
-            # model_id
-            cache_path = cached_assets_path(
-                library_name="transformers", namespace=model_path
-            )
-
         if load_detokenizer:
             logger.info(f"Loading detokenizer")
             # need to compile extension moudules for the first time, it may take several minutes.

kimia_infer/api/prompt_manager.py

@@ -4,7 +4,6 @@ import os
 import librosa
 import torch
 from loguru import logger
-from huggingface_hub import cached_assets_path
 from transformers import AutoTokenizer
 
 
@@ -13,25 +12,16 @@ from kimia_infer.models.tokenizer.glm4_tokenizer import Glm4Tokenizer
 from kimia_infer.utils.data import KimiAContent
 from kimia_infer.utils.special_tokens import instantiate_extra_tokens
 
-
 class KimiAPromptManager:
     def __init__(self, model_path: str, kimia_token_offset: int):
         self.audio_tokenizer = Glm4Tokenizer("THUDM/glm-4-voice-tokenizer")
         self.audio_tokenizer = self.audio_tokenizer.to(torch.cuda.current_device())
 
-        if os.path.exists(model_path):
-            # local path
-            cache_path = model_path
-        else:
-            # model_id
-            cache_path = cached_assets_path(
-                library_name="transformers", namespace=model_path
-            )
-        logger.info(f"Looking for resources in {cache_path}")
+        logger.info(f"Looking for resources in {model_path}")
         logger.info(f"Loading whisper model")
 
         self.whisper_model = WhisperEncoder(
-            os.path.join(cache_path, "whisper-large-v3"), mel_batch_size=20
+            os.path.join(model_path, "whisper-large-v3"), mel_batch_size=20
         )
         self.whisper_model = self.whisper_model.to(torch.cuda.current_device())
         self.whisper_model = self.whisper_model.bfloat16()