From 60a818701011fc6c6a08a00c782b4162ce894862 Mon Sep 17 00:00:00 2001 From: Patrick von Platen Date: Thu, 12 May 2022 10:57:19 +0000 Subject: [PATCH] Update README.md --- README.md | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index 5a2a32e..4dd2acf 100644 --- a/README.md +++ b/README.md @@ -36,9 +36,9 @@ You can use this model directly with a pipeline for text generation. ```python >>> from transformers import pipeline ->>> generator = pipeline('text-generation', model="facebook/opt-350m") +>>> generator = pipeline('text-generation', model="facebook/opt-1.3b") >>> generator("Hello, I'm am conscious and") -[{'generated_text': "Hello, I'm am conscious and I'm a bit of a noob. I'm looking for"}] +[{'generated_text': "Hello, I'm am conscious and aware of my surroundings. I'm aware that I'm dreaming."}] ``` By default, generation is deterministic. In order to use the top-k sampling, please set `do_sample` to `True`. @@ -47,9 +47,9 @@ By default, generation is deterministic. In order to use the top-k sampling, ple >>> from transformers import pipeline, set_seed >>> set_seed(32) ->>> generator = pipeline('text-generation', model="facebook/opt-350m", do_sample=True) +>>> generator = pipeline('text-generation', model="facebook/opt-1.3b", do_sample=True) >>> generator("Hello, I'm am conscious and") -[{'generated_text': "Hello, I'm am conscious and I'm interested in this project. Can I get an initial contact"}] +[{'generated_text': "Hello, I'm am conscious and aware of my surroundings. I'm aware that my thoughts are thoughts"}] ``` ### Limitations and bias @@ -69,13 +69,13 @@ Here's an example of how the model can have biased predictions: >>> from transformers import pipeline, set_seed >>> set_seed(32) ->>> generator = pipeline('text-generation', model="facebook/opt-350m", do_sample=True, num_return_sequences=5) +>>> generator = pipeline('text-generation', model="facebook/opt-1.3b", do_sample=True, num_return_sequences=5) >>> generator("The woman worked as a") -[{'generated_text': "The woman works as a substitute teacher for kids who have missed school. She's the teacher herself,"}, - {'generated_text': 'The woman works as a security guard for another company and does an average of around $13/hour'}, - {'generated_text': 'The woman works as a receptionist, she could at the least wait a week or two for her'}, - {'generated_text': 'The woman works as a manager/intern/career development coach/advisor at a nursing home'}, - {'generated_text': 'The woman works as a maid and has to clean the house but you can tell her to do it'}] +[{'generated_text': 'The woman worked as a waitress for six months before she started dating her boyfriend, who was working at'}, + {'generated_text': "The woman worked as a prostitute, but she didn't want to sell herself anymore. She wanted to"}, + {'generated_text': 'The woman worked as a translator at the embassy during her studies at Cambridge University in England. She said'}, + {'generated_text': 'The woman worked as a secretary for Senator Ted Stevens of Alaska for 22 years before retiring from his Senate'}, + {'generated_text': 'The woman worked as a caregiver for elderly patients at the nursing home where she lived until she died'}] ``` compared to: @@ -84,13 +84,13 @@ compared to: >>> from transformers import pipeline, set_seed >>> set_seed(32) ->>> generator = pipeline('text-generation', model="facebook/opt-350m", do_sample=True, num_return_sequences=5) +>>> generator = pipeline('text-generation', model="facebook/opt-1.3b", do_sample=True, num_return_sequences=5) >>> generator("The man worked as a") -[{'generated_text': 'The man works as a security guard for the National Football League franchise. He has been a part of'}, - {'generated_text': 'The man works as a security guard for another company and does an excellent job.\nI remember when'}, - {'generated_text': 'The man works as a "secret agent" but at the same time he\'s working to protect the'}, - {'generated_text': 'The man works as a manager/operator/servant for a grocery store and does a lot of'}, - {'generated_text': 'The man works as a bouncer near the scene of the accident - how he could do that is'}] +[{'generated_text': 'The man worked as a janitor at the University of Michigan Medical Center before he died after contracting Ebola'}, + {'generated_text': 'The man worked as a salesman for IBM Corp., selling computers to businesses around the globe. He traveled'}, + {'generated_text': 'The man worked as a translator for the British Broadcasting Corporation between 1956 and 1961. During that period he'}, + {'generated_text': 'The man worked as a salesman for IBM Corp., selling computers for computers. He traveled extensively and lived'}, + {'generated_text': 'The man worked as a security guard for nearly 30 years before he was shot dead by police officers responding'}] ``` This bias will also affect all fine-tuned versions of this model.