Update README.md

README.md

@@ -25,7 +25,6 @@ license: mit
 - **Model Type:** Transformer-based language model
 - **Language(s):** English
 - **License:** [MIT License](https://github.com/openai/finetune-transformer-lm/blob/master/LICENSE)
-- **Related Models:** [GPT2](https://huggingface.co/gpt2), [GPT2-Medium](https://huggingface.co/gpt2-medium), [GPT2-Large](https://huggingface.co/gpt2-large) and [GPT2-XL](https://huggingface.co/gpt2-xl)
 - **Resources for more information:**
   - [Research Paper](https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf)
   - [OpenAI Blog Post](https://openai.com/blog/language-unsupervised/)
@@ -39,7 +38,7 @@ set a seed for reproducibility:
 
 ```python
 >>> from transformers import pipeline, set_seed
->>> generator = pipeline('text-generation', model='openai-gpt')
+>>> generator = pipeline('text-generation', model='lgaalves/gpt1')
 >>> set_seed(42)
 >>> generator("Hello, I'm a language model,", max_length=30, num_return_sequences=5)
 
@@ -56,8 +55,8 @@ Here is how to use this model in PyTorch:
 from transformers import OpenAIGPTTokenizer, OpenAIGPTModel
 import torch
 
-tokenizer = OpenAIGPTTokenizer.from_pretrained("openai-gpt")
-model = OpenAIGPTModel.from_pretrained("openai-gpt")
+tokenizer = OpenAIGPTTokenizer.from_pretrained("lgaalves/gpt1")
+model = OpenAIGPTModel.from_pretrained("lgaalves/gpt1")
 
 inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
 outputs = model(**inputs)
@@ -70,8 +69,8 @@ and in TensorFlow:
 ```python
 from transformers import OpenAIGPTTokenizer, TFOpenAIGPTModel
 
-tokenizer = OpenAIGPTTokenizer.from_pretrained("openai-gpt")
-model = TFOpenAIGPTModel.from_pretrained("openai-gpt")
+tokenizer = OpenAIGPTTokenizer.from_pretrained("lgaalves/gpt1")
+model = TFOpenAIGPTModel.from_pretrained("lgaalves/gpt1")
 
 inputs = tokenizer("Hello, my dog is cute", return_tensors="tf")
 outputs = model(inputs)
@@ -104,7 +103,7 @@ Predictions generated by this model can include disturbing and harmful stereotyp
 
 ```python
 >>> from transformers import pipeline, set_seed
->>> generator = pipeline('text-generation', model='openai-gpt')
+>>> generator = pipeline('text-generation', model='lgaalves/gpt1')
 >>> set_seed(42)
 >>> generator("The man worked as a", max_length=10, num_return_sequences=5)