# GPT Neo ## Overview The GPTNeo model was released in the [EleutherAI/gpt-neo](https://github.com/EleutherAI/gpt-neo) repository by Sid Black, Stella Biderman, Leo Gao, Phil Wang and Connor Leahy. It is a GPT2 like causal language model trained on the [Pile](https://pile.eleuther.ai/) dataset. The architecture is similar to GPT2 except that GPT Neo uses local attention in every other layer with a window size of 256 tokens. This model was contributed by [valhalla](https://huggingface.co/valhalla). ### Generation The `generate()` method can be used to generate text using GPT Neo model. ```python >>> from transformers import GPTNeoForCausalLM, GPT2Tokenizer >>> model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B") >>> tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B") >>> prompt = ( ... "In a shocking finding, scientists discovered a herd of unicorns living in a remote, " ... "previously unexplored valley, in the Andes Mountains. Even more surprising to the " ... "researchers was the fact that the unicorns spoke perfect English." ... ) >>> input_ids = tokenizer(prompt, return_tensors="pt").input_ids >>> gen_tokens = model.generate( ... input_ids, ... do_sample=True, ... temperature=0.9, ... max_length=100, ... ) >>> gen_text = tokenizer.batch_decode(gen_tokens)[0] ``` ## Documentation resources - [Text classification task guide](../tasks/sequence_classification) - [Causal language modeling task guide](../tasks/language_modeling) ## GPTNeoConfig [[autodoc]] GPTNeoConfig ## GPTNeoModel [[autodoc]] GPTNeoModel - forward ## GPTNeoForCausalLM [[autodoc]] GPTNeoForCausalLM - forward ## GPTNeoForQuestionAnswering [[autodoc]] GPTNeoForQuestionAnswering - forward ## GPTNeoForSequenceClassification [[autodoc]] GPTNeoForSequenceClassification - forward ## GPTNeoForTokenClassification [[autodoc]] GPTNeoForTokenClassification - forward ## FlaxGPTNeoModel [[autodoc]] FlaxGPTNeoModel - __call__ ## FlaxGPTNeoForCausalLM [[autodoc]] FlaxGPTNeoForCausalLM - __call__