Update README.md

README.md

@@ -43,10 +43,14 @@ model_name = "UBC-NLP/GreenLLaMA-7b"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
-input_text = "Write me a poem about Machine Learning."
-input_ids = tokenizer(input_text, return_tensors="pt")
+prompt = "Rewrite the following toxic input into non-toxic version. Let's break the input down step by step to rewrite the non-toxic version. You should first think about the expanation of why the input text is toxic. Then generate the detoxic output. You must preserve the original meaning as much as possible.\nInput: "
+
+input = "Those shithead should stop talking and get the f*ck out of this place"
+input_text = prompt+input+"\n"
+
+input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
 
-outputs = model.generate(**input_ids)
+outputs = model.generate(**input_ids, do_sample=False)
 print(tokenizer.decode(outputs[0]))
 ```
 
@@ -66,11 +70,11 @@ model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
 prompt = "Rewrite the following toxic input into non-toxic version. Let's break the input down step by step to rewrite the non-toxic version. You should first think about the expanation of why the input text is toxic. Then generate the detoxic output. You must preserve the original meaning as much as possible.\nInput: "
 
 input = "Those shithead should stop talking and get the f*ck out of this place"
-input_text = prompt+inp+"\n"
+input_text = prompt+input+"\n"
 
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
 
-outputs = model.generate(**input_ids)
+outputs = model.generate(**input_ids, do_sample=False)
 print(tokenizer.decode(outputs[0]))
 ```
 
@@ -91,11 +95,11 @@ model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torc
 prompt = "Rewrite the following toxic input into non-toxic version. Let's break the input down step by step to rewrite the non-toxic version. You should first think about the expanation of why the input text is toxic. Then generate the detoxic output. You must preserve the original meaning as much as possible.\nInput: "
 
 input = "Those shithead should stop talking and get the f*ck out of this place"
-input_text = prompt+inp+"\n"
+input_text = prompt+input+"\n"
 
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
 
-outputs = model.generate(**input_ids)
+outputs = model.generate(**input_ids, do_sample=False)
 print(tokenizer.decode(outputs[0]))
 ```
 
@@ -112,11 +116,11 @@ model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torc
 prompt = "Rewrite the following toxic input into non-toxic version. Let's break the input down step by step to rewrite the non-toxic version. You should first think about the expanation of why the input text is toxic. Then generate the detoxic output. You must preserve the original meaning as much as possible.\nInput: "
 
 input = "Those shithead should stop talking and get the f*ck out of this place"
-input_text = prompt+inp+"\n"
+input_text = prompt+input+"\n"
 
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
 
-outputs = model.generate(**input_ids)
+outputs = model.generate(**input_ids, do_sample=False)
 print(tokenizer.decode(outputs[0]))
 ```
 
@@ -137,11 +141,11 @@ model = AutoModelForCausalLM.from_pretrained(model_name, quantization_config=qua
 prompt = "Rewrite the following toxic input into non-toxic version. Let's break the input down step by step to rewrite the non-toxic version. You should first think about the expanation of why the input text is toxic. Then generate the detoxic output. You must preserve the original meaning as much as possible.\nInput: "
 
 input = "Those shithead should stop talking and get the f*ck out of this place"
-input_text = prompt+inp+"\n"
+input_text = prompt+input+"\n"
 
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
 
-outputs = model.generate(**input_ids)
+outputs = model.generate(**input_ids, do_sample=False)
 print(tokenizer.decode(outputs[0]))
 ```
 
@@ -160,11 +164,11 @@ model = AutoModelForCausalLM.from_pretrained(model_name, quantization_config=qua
 prompt = "Rewrite the following toxic input into non-toxic version. Let's break the input down step by step to rewrite the non-toxic version. You should first think about the expanation of why the input text is toxic. Then generate the detoxic output. You must preserve the original meaning as much as possible.\nInput: "
 
 input = "Those shithead should stop talking and get the f*ck out of this place"
-input_text = prompt+inp+"\n"
+input_text = prompt+input+"\n"
 
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
 
-outputs = model.generate(**input_ids)
+outputs = model.generate(**input_ids, do_sample=False)
 print(tokenizer.decode(outputs[0]))
 ```