Upload model

config.json

@@ -1,18 +1,13 @@
 {
-  "architectures": [
-    "SpeechLLMModel"
-  ],
   "audio_enc_dim": 1280,
   "audio_encoder_name": "facebook/hubert-xlarge-ll60k",
   "audio_processor_name": "facebook/hubert-large-ls960-ft",
   "auto_map": {
-    "AutoConfig": "config.SpeechLLMModelConfig",
-    "AutoModel": "model.SpeechLLMModel"
+    "AutoConfig": "config.SpeechLLMModelConfig"
   },
   "llm_dim": 2048,
   "llm_model_checkpoint": "hf_repo/llm_model_checkpoint",
   "llm_model_name": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
   "model_type": "custom_model",
-  "torch_dtype": "float32",
   "transformers_version": "4.38.2"
 }

config.py

@@ -1,4 +1,3 @@
-import os
 from transformers import PretrainedConfig
 
 class SpeechLLMModelConfig(PretrainedConfig):
@@ -12,4 +11,4 @@ class SpeechLLMModelConfig(PretrainedConfig):
         self.audio_processor_name = "facebook/hubert-large-ls960-ft"
         self.audio_encoder_name = 'facebook/hubert-xlarge-ll60k'
         self.llm_model_name = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
-        self.llm_model_checkpoint = os.path.join(os.path.dirname(__file__), "lora_checkpoint")
+        self.llm_model_checkpoint = "hf_repo/llm_model_checkpoint"