gpt_neo.rst

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    Copyright 2021 The HuggingFace Team. All rights reserved.

    Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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        http://www.apache.org/licenses/LICENSE-2.0

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GPT Neo
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Overview
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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
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The :obj:`generate()` method can be used to generate text using GPT Neo model.

.. code-block::

    >>> 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]


GPTNeoConfig
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.. autoclass:: transformers.GPTNeoConfig
    :members:


GPTNeoModel
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.. autoclass:: transformers.GPTNeoModel
    :members: forward


GPTNeoForCausalLM
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.. autoclass:: transformers.GPTNeoForCausalLM
    :members: forward

GPTNeoForSequenceClassification
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.. autoclass:: transformers.GPTNeoForSequenceClassification
    :members: forward

FlaxGPTNeoModel
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.. autoclass:: transformers.FlaxGPTNeoModel
    :members: __call__


FlaxGPTNeoForCausalLM
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.. autoclass:: transformers.FlaxGPTNeoForCausalLM
    :members: __call__