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Monimoy commited on
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1 Parent(s): 7cd74fe

Upload app.py

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  1. app.py +2 -2
app.py CHANGED
@@ -15,7 +15,7 @@ peft_model_path = "./phi2-openassistant-lora-final"
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  # Load the base model with 4-bit quantization
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  #bnb_config = BitsAndBytesConfig(load_in_4bit=True) # Ensure compatibility
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  #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, quantization_config=bnb_config, device_map={"": device})
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- #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, torch_dtype=torch.float32, device_map={"": device})
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  #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, load_in_4bit=True, device_map={"": device})
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  #bnb_config = BitsAndBytesConfig(
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  #load_in_4bit=True,
@@ -25,7 +25,7 @@ peft_model_path = "./phi2-openassistant-lora-final"
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  #)
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  #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, quantization_config=bnb_config, device_map={"": device})
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  #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, model_type="llama", device_map={"": device}, quantization="4bit")
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- base_model = AutoModelForCausalLM.from_pretrained(base_model_name, load_in_4bit=True, device_map={"": device}, torch_dtype=torch.float16)
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  # Load the base model with 4-bit quantization
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  #bnb_config = BitsAndBytesConfig(load_in_4bit=True) # Ensure compatibility
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  #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, quantization_config=bnb_config, device_map={"": device})
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+ base_model = AutoModelForCausalLM.from_pretrained(base_model_name, torch_dtype=torch.float32, device_map={"": device})
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  #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, load_in_4bit=True, device_map={"": device})
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  #bnb_config = BitsAndBytesConfig(
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  #load_in_4bit=True,
 
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  #)
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  #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, quantization_config=bnb_config, device_map={"": device})
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  #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, model_type="llama", device_map={"": device}, quantization="4bit")
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+ #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, load_in_4bit=True, device_map={"": device}, torch_dtype=torch.float16)
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