# What does this PR do?

I have replaced the assert statements with appropriate exceptions in the directory `src/transformers/models/` with all models beginning with `a` and `b` letters.

Also, I have corrected error handling at places where except statements were handling AssertionError, even thought it was never to be raised. Here is an example:

```
try:
    if pointer.shape != array.shape:
        raise ValueError(f"Pointer shape {pointer.shape} and array shape {array.shape} mismatched")
except AssertionError as e:    # Incorrect line
    e.args += (pointer.shape, array.shape)
    raise
```

I changed the above to:

```
try:
    if pointer.shape != array.shape:
        raise ValueError(f"Pointer shape {pointer.shape} and array shape {array.shape} mismatched")
except ValueError as e:    # Corrected the line
    e.args += (pointer.shape, array.shape)
    raise
```

Fixes #12789 


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [x] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

@ArthurZucker @sgugger 

Replace assert statements with exceptions. # What does this PR do?

I have replaced the assert statements with appropriate exceptions in the directory `src/transformers/models/` with all models beginning with `a` and `b` letters.

Also, I have corrected error handling at places where except statements were handling AssertionError, even thought it was never to be raised. Here is an example:

```
try:
    if pointer.shape != array.shape:
        raise ValueError(f"Pointer shape {pointer.shape} and array shape {array.shape} mismatched")
except AssertionError as e:    # Incorrect line
    e.args += (pointer.shape, array.shape)
    raise
```

I changed the above to:

```
try:
    if pointer.shape != array.shape:
        raise ValueError(f"Pointer shape {pointer.shape} and array shape {array.shape} mismatched")
except ValueError as e:    # Corrected the line
    e.args += (pointer.shape, array.shape)
    raise
```

Fixes #12789 


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [x] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

@ArthurZucker @sgugger 

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⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
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# 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__

<!--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
the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.

⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.

-->

# 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__
