Update README.md

README.md

@@ -74,7 +74,7 @@ def llmCompletion(prompt, **args):
     response = requests.post(url, headers=headers, json=data)
     return response.json()
 
-def analyze_argument2(argument):
+def analyze_argument(argument):
     instruction = 'Based on the following argument, identify the following elements: premises, conclusion, propositions, type of argument, negation of propositions and validity.'
     alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
 
@@ -134,9 +134,9 @@ First make sure to pip install -U transformers, then use the code below replacin
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model = AutoModelForCausalLM.from_pretrained("./model_gguf", 
+model = AutoModelForCausalLM.from_pretrained("cris177/Qwen2-Simple-Arguments", 
     device_map="auto",)
-tokenizer = AutoTokenizer.from_pretrained("./model_gguf")
+tokenizer = AutoTokenizer.from_pretrained("cris177/Qwen2-Simple-Arguments")
 
 argument = "If it's wednesday it's cold, and it's cold, therefore it's wednesday."