Update README.md

README.md

@@ -96,7 +96,7 @@ def generate_prompt(instruction: str, input_ctxt: str = None) -> str:
 
 Use the code below to get started with the model.
 
-1. You can git clone the repo, which contains also the artifacts for the base model for simplicity and completeness, and run the following code snippet to load the mode:
+1. You can directly call the model from HuggingFace using the following code snippet:
 
 ```python
 import torch
@@ -104,11 +104,12 @@ from peft import PeftConfig, PeftModel
 from transformers import GenerationConfig, LlamaTokenizer, LlamaForCausalLM
 
 MODEL_NAME = "Sandiago21/llama-13b-hf-prompt-answering"
+BASE_MODEL = "decapoda-research/llama-13b-hf"
 
 config = PeftConfig.from_pretrained(MODEL_NAME)
 
 model = LlamaForCausalLM.from_pretrained(
- config.base_model_name_or_path,
+ BASE_MODEL,
  load_in_8bit=True,
  torch_dtype=torch.float16,
  device_map="auto",
@@ -154,7 +155,7 @@ print(response)
 >>> The capital city of Greece is Athens and it borders Turkey, Bulgaria, Macedonia, Albania, and the Aegean Sea.
 ```
 
-2. You can also directly call the model from HuggingFace using the following code snippet:
+1. You can git clone the repo, which contains also the artifacts for the base model for simplicity and completeness, and run the following code snippet to load the mode:
 
 ```python
 import torch
@@ -162,12 +163,11 @@ from peft import PeftConfig, PeftModel
 from transformers import GenerationConfig, LlamaTokenizer, LlamaForCausalLM
 
 MODEL_NAME = "Sandiago21/llama-13b-hf-prompt-answering"
-BASE_MODEL = "decapoda-research/llama-13b-hf"
 
 config = PeftConfig.from_pretrained(MODEL_NAME)
 
 model = LlamaForCausalLM.from_pretrained(
- BASE_MODEL,
+ config.base_model_name_or_path,
  load_in_8bit=True,
  torch_dtype=torch.float16,
  device_map="auto",
@@ -213,6 +213,7 @@ print(response)
 >>> The capital city of Greece is Athens and it borders Turkey, Bulgaria, Macedonia, Albania, and the Aegean Sea.
 ```
 
+
 ## Training Details
 
 ## Training procedure