fix: Add workaround for incorrect base model path

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 import torch
-from transformers import AutoTokenizer, TextIteratorStreamer, AutoModelForCausalLM
+from transformers import AutoTokenizer, TextIteratorStreamer, AutoModelForCausalLM, AutoConfig
 import requests
 import json
 from peft import PeftModel
@@ -24,9 +24,18 @@ if not hf_token:
 # Load the tokenizer from the Hub, using the token for private models
 tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL_PATH, use_auth_token=hf_token)
 
-# Load the base model from the Hub
+from transformers import AutoConfig
+
+# Load the config from the user's repo
+config = AutoConfig.from_pretrained(BASE_MODEL_PATH, use_auth_token=hf_token)
+
+# Correct the base model path in the config
+config._name_or_path = "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct"
+
+# Load the base model from the Hub using the corrected config
 base_model = AutoModelForCausalLM.from_pretrained(
     BASE_MODEL_PATH,
+    config=config,
     trust_remote_code=True,
     low_cpu_mem_usage=True,
     torch_dtype=torch.bfloat16,