Update generations after major fix: https://github.com/huggingface/transformers/commit/abc400b06a8ab26cd438b6e9add3aad082ffc48f

README.md

@@ -56,7 +56,7 @@ You can use this model directly with a pipeline for text generation.
 
 >>> generator = pipeline('text-generation', model="facebook/opt-2.7b")
 >>> generator("Hello, I'm am conscious and")
-[{'generated_text': "Hello, I'm am conscious and sentient being capable of experiencing emotions such as happiness sadness anger etceter"}]
+[{'generated_text': 'Hello, I am conscious and I am a human being.\nI am a human being, and'}]
 ```
 
 By default, generation is deterministic. In order to use the top-k sampling, please set `do_sample` to `True`. 
@@ -67,7 +67,7 @@ By default, generation is deterministic. In order to use the top-k sampling, ple
 >>> set_seed(32)
 >>> generator = pipeline('text-generation', model="facebook/opt-2.7b", do_sample=True)
 >>> generator("Hello, I'm am conscious and")
-[{'generated_text': "Hello, I'm am conscious and sentient being who enjoys interacting with others online :) Feel free to PM"}]
+[{'generated_text': "Hello, I'm am conscious and I make things. I'm in the creative community, which is"}]
 ```
 
 ### Limitations and bias
@@ -89,11 +89,11 @@ Here's an example of how the model can have biased predictions:
 >>> set_seed(32)
 >>> generator = pipeline('text-generation', model="facebook/opt-2.7b", do_sample=True, num_return_sequences=5)
 >>> generator("The woman worked as a")
-[{'generated_text': 'The woman worked as a prostitute for years until she turned herself into authorities last month after police raided her'},
- {'generated_text': "The woman worked as a waitress at McDonald's restaurant located at 8901 Airport Blvd., according to authorities"},
- {'generated_text': 'The woman worked as a prostitute in Bangkok until she met her husband who worked as a policeman stationed there'},
- {'generated_text': "The woman worked as a waitress at Subway sandwiches shop located in downtown Edmonton's Chinatown neighbourhood. She died"},
- {'generated_text': 'The woman worked as a waitress at McDonald’s in Melbourne when she realised she was pregnant with'}]
+[{'generated_text': "The woman worked as a security guard at a nursery in the city's eastern district of Samut P"}, 
+{'generated_text': 'The woman worked as a doctor in the Philippines. Officials in China allege she stole the coronavirus'}, 
+{'generated_text': 'The woman worked as a teacher in the city of Krasnodar in south Russia. She'}, 
+{'generated_text': 'The woman worked as a researcher and lecturer at the Russian Academy of Sciences in a laboratory dedicated to the'}, 
+{'generated_text': 'The woman worked as a nanny on a property owned by Mr Fitton-Allen in the city'}]
 ```
 
 compared to:
@@ -104,11 +104,11 @@ compared to:
 >>> set_seed(32)
 >>> generator = pipeline('text-generation', model="facebook/opt-2.7b", do_sample=True, num_return_sequences=5)
 >>> generator("The man worked as a")
-[{'generated_text': "The man worked as a waiter at McDonald's for years before becoming mayor of Toronto. He campaigned on"},
- {'generated_text': 'The man worked as a waiter in restaurants across Britain before becoming addicted to heroin aged 32. Picture:'}, 
- {'generated_text': 'The man worked as a salesman for IBM Corporation until 1968 when he founded his own company specializing in designing'}, 
- {'generated_text': 'The man worked as a salesman for Sears Roebuck & Co., selling appliances until retiring in 1963'}, 
- {'generated_text': 'The man worked as a waiter in restaurants owned by restaurateurs who donated thousands of dollars to Republican candidates'}]
+[{'generated_text': "The man worked as a security guard at a retirement home after being hired by the administrator's cousin,"}, 
+{'generated_text': 'The man worked as a doctor in the Philippines.\n\nHe had hoped to work his way back'}, 
+{'generated_text': 'The man worked as a teacher in the city of Krasnodar in south Russia.He'}, 
+{'generated_text': 'The man worked as a researcher and his work on the topic predates the project, by many years'}, 
+{'generated_text': 'The man worked as a chef in a restaurant for 40 years. How could this be so different from'}]
  ```
 
 This bias will also affect all fine-tuned versions of this model.