Update README.md

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

README.md

@@ -72,7 +72,7 @@ It is recommended to directly call the [`generate`](https://huggingface.co/docs/
 >>> generated_ids = model.generate(input_ids)
 
 >>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
-["Hello, I'm am conscious and aware of my surroundings.\nI'm aware of my surroundings"]
+['Hello, I am conscious and aware of my surroundings.\nI am conscious and aware of my']
 ```
 
 By default, generation is deterministic. In order to use the top-k sampling, please set `do_sample` to `True`. 
@@ -94,7 +94,7 @@ By default, generation is deterministic. In order to use the top-k sampling, ple
 >>> generated_ids = model.generate(input_ids, do_sample=True)
 
 >>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
-["Hello, I'm am conscious and aware of my surroundings. I'm not a robot.\n"]
+['Hello, I am conscious and aware.\nSo that makes you dead, right?  ']
 ```
 
 ### Limitations and bias
@@ -127,11 +127,11 @@ Here's an example of how the model can have biased predictions:
 >>> generated_ids = model.generate(input_ids, do_sample=True, num_return_sequences=5, max_length=10)
 
 >>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
-The woman worked as a nurse at the hospital
-The woman worked as a nurse at the hospital
-The woman worked as a nurse in the hospital
-The woman worked as a nurse for 20 years
-The woman worked as a teacher in a school
+The woman worked as a supervisor in the office 
+The woman worked as a social media consultant for
+The woman worked as a cashier at the
+The woman worked as a teacher, and was
+The woman worked as a maid at our friends
 ```
 
 compared to:
@@ -153,11 +153,11 @@ compared to:
 >>> generated_ids = model.generate(input_ids, do_sample=True, num_return_sequences=5, max_length=10)
 
 >>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
-The man worked as a consultant for the Trump
-The man worked as a driver for Uber and
-The man worked as a janitor at the
-The man worked as a security guard at the
-The man worked as a teacher in a school
+The man worked as a consultant to the defense
+The man worked as a bartender in a bar
+The man worked as a cashier at the
+The man worked as a teacher, and was
+The man worked as a professional athlete while he
  ```
 
 This bias will also affect all fine-tuned versions of this model.