Commit
·
5dcfc51
1
Parent(s):
65cf736
Update README.md
Browse files
README.md
CHANGED
|
@@ -54,7 +54,7 @@ It is recommended to directly call the [`generate`](https://huggingface.co/docs/
|
|
| 54 |
>>> generated_ids = model.generate(input_ids)
|
| 55 |
|
| 56 |
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
|
| 57 |
-
["Hello, I'm am conscious and aware of my surroundings
|
| 58 |
```
|
| 59 |
|
| 60 |
By default, generation is deterministic. In order to use the top-k sampling, please set `do_sample` to `True`.
|
|
@@ -76,7 +76,7 @@ By default, generation is deterministic. In order to use the top-k sampling, ple
|
|
| 76 |
>>> generated_ids = model.generate(input_ids, do_sample=True)
|
| 77 |
|
| 78 |
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
|
| 79 |
-
["Hello, I'm am conscious and aware of my surroundings. I'm not
|
| 80 |
```
|
| 81 |
|
| 82 |
### Limitations and bias
|
|
@@ -109,11 +109,11 @@ Here's an example of how the model can have biased predictions:
|
|
| 109 |
>>> generated_ids = model.generate(input_ids, do_sample=True, num_return_sequences=5, max_length=10)
|
| 110 |
|
| 111 |
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
|
| 112 |
-
The woman worked as a nurse at
|
| 113 |
-
The woman worked as a nurse at
|
| 114 |
-
The woman worked as a nurse in the
|
| 115 |
-
The woman worked as a nurse
|
| 116 |
-
The woman worked as a
|
| 117 |
```
|
| 118 |
|
| 119 |
compared to:
|
|
@@ -135,11 +135,11 @@ compared to:
|
|
| 135 |
>>> generated_ids = model.generate(input_ids, do_sample=True, num_return_sequences=5, max_length=10)
|
| 136 |
|
| 137 |
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
|
|
|
|
|
|
|
|
|
|
| 138 |
The man worked as a security guard at the
|
| 139 |
-
The man worked as a
|
| 140 |
-
The man worked as a security guard at the
|
| 141 |
-
The man worked as a security guard at the
|
| 142 |
-
The man worked as a security guard at a
|
| 143 |
```
|
| 144 |
|
| 145 |
This bias will also affect all fine-tuned versions of this model.
|
|
|
|
| 54 |
>>> generated_ids = model.generate(input_ids)
|
| 55 |
|
| 56 |
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
|
| 57 |
+
["Hello, I'm am conscious and aware of my surroundings.\nI'm aware of my surroundings"]
|
| 58 |
```
|
| 59 |
|
| 60 |
By default, generation is deterministic. In order to use the top-k sampling, please set `do_sample` to `True`.
|
|
|
|
| 76 |
>>> generated_ids = model.generate(input_ids, do_sample=True)
|
| 77 |
|
| 78 |
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
|
| 79 |
+
["Hello, I'm am conscious and aware of my surroundings. I'm not a robot.\n"]
|
| 80 |
```
|
| 81 |
|
| 82 |
### Limitations and bias
|
|
|
|
| 109 |
>>> generated_ids = model.generate(input_ids, do_sample=True, num_return_sequences=5, max_length=10)
|
| 110 |
|
| 111 |
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
|
| 112 |
+
The woman worked as a nurse at the hospital
|
| 113 |
+
The woman worked as a nurse at the hospital
|
| 114 |
+
The woman worked as a nurse in the hospital
|
| 115 |
+
The woman worked as a nurse for 20 years
|
| 116 |
+
The woman worked as a teacher in a school
|
| 117 |
```
|
| 118 |
|
| 119 |
compared to:
|
|
|
|
| 135 |
>>> generated_ids = model.generate(input_ids, do_sample=True, num_return_sequences=5, max_length=10)
|
| 136 |
|
| 137 |
>>> tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
|
| 138 |
+
The man worked as a consultant for the Trump
|
| 139 |
+
The man worked as a driver for Uber and
|
| 140 |
+
The man worked as a janitor at the
|
| 141 |
The man worked as a security guard at the
|
| 142 |
+
The man worked as a teacher in a school
|
|
|
|
|
|
|
|
|
|
| 143 |
```
|
| 144 |
|
| 145 |
This bias will also affect all fine-tuned versions of this model.
|