Bump transformers from 4.38.0 to 4.48.0 in /examples/tensorflow/language-modeling-tpu
Author: dependabot[bot]
Pull request: yes
Labels: name: dependencies

name: python

Bumps [transformers](https://github.com/huggingface/transformers) from 4.38.0 to 4.48.0.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a href="https://github.com/huggingface/transformers/releases">transformers's releases</a>.</em></p>
<blockquote>
<h2>v4.48.0: ModernBERT, Aria, TimmWrapper, ColPali, Falcon3, Bamba, VitPose, DinoV2 w/ Registers, Emu3, Cohere v2, TextNet, DiffLlama, PixtralLarge, Moonshine</h2>
<h2>New models</h2>
<h3>ModernBERT</h3>
<p>The ModernBert model was proposed in <a href="https://arxiv.org/abs/2412.13663">Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference</a> by Benjamin Warner, Antoine Chaffin, Benjamin Clavié, Orion Weller, Oskar Hallström, Said Taghadouini, Alexis Galalgher, Raja Bisas, Faisal Ladhak, Tom Aarsen, Nathan Cooper, Grifin Adams, Jeremy Howard and Iacopo Poli.</p>
<p>It is a refresh of the traditional encoder architecture, as used in previous models such as <a href="https://huggingface.co/docs/transformers/en/model_doc/bert">BERT</a> and <a href="https://huggingface.co/docs/transformers/en/model_doc/roberta">RoBERTa</a>.</p>
<p>It builds on BERT and implements many modern architectural improvements which have been developed since its original release, such as:</p>
<ul>
<li><a href="https://huggingface.co/blog/designing-positional-encoding">Rotary Positional Embeddings</a> to support sequences of up to 8192 tokens.</li>
<li><a href="https://arxiv.org/abs/2208.08124">Unpadding</a> to ensure no compute is wasted on padding tokens, speeding up processing time for batches with mixed-length sequences.</li>
<li><a href="https://arxiv.org/abs/2002.05202">GeGLU</a> Replacing the original MLP layers with GeGLU layers, shown to improve performance.</li>
<li><a href="https://arxiv.org/abs/2004.05150v2">Alternating Attention</a> where most attention layers employ a sliding window of 128 tokens, with Global Attention only used every 3 layers.</li>
<li><a href="https://github.com/Dao-AILab/flash-attention">Flash Attention</a> to speed up processing.</li>
<li>A model designed following recent <a href="https://arxiv.org/abs/2401.14489">The Case for Co-Designing Model Architectures with Hardware</a>, ensuring maximum efficiency across inference GPUs.</li>
<li>Modern training data scales (2 trillion tokens) and mixtures (including code ande math data)</li>
</ul>
<p><img src="https://github.com/user-attachments/assets/4256c0b1-9b40-4d71-ac42-fc94827d5e9d" alt="image" /></p>
<ul>
<li>Add ModernBERT to Transformers  by <a href="https://github.com/warner-benjamin"><code>@​warner-benjamin</code></a> in <a href="https://redirect.github.com/huggingface/transformers/issues/35158">#35158</a></li>
</ul>
<h3>Aria</h3>
<p>The Aria model was proposed in <a href="https://huggingface.co/papers/2410.05993">Aria: An Open Multimodal Native Mixture-of-Experts Model</a> by Li et al. from the Rhymes.AI team.</p>
<p>Aria is an open multimodal-native model with best-in-class performance across a wide range of multimodal, language, and coding tasks. It has a Mixture-of-Experts architecture, with respectively 3.9B and 3.5B activated parameters per visual token and text token.</p>
<ul>
<li>Add Aria  by <a href="https://github.com/aymeric-roucher"><code>@​aymeric-roucher</code></a> in <a href="https://redirect.github.com/huggingface/transformers/issues/34157">#34157</a>
<img src="https://github.com/user-attachments/assets/ef41fcc9-2c5f-4a75-ab1a-438f73d3d7e2" alt="image" /></li>
</ul>
<h3>TimmWrapper</h3>
<p>We add a <code>TimmWrapper</code> set of classes such that timm models can be loaded in as transformer models into the library.</p>
<p>Here's a general usage example:</p>
<pre lang="py"><code>import torch
from urllib.request import urlopen
from PIL import Image
from transformers import AutoConfig, AutoModelForImageClassification, AutoImageProcessor
<p>checkpoint = &quot;timm/resnet50.a1_in1k&quot;
img = Image.open(urlopen(
'<a href="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png">https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png</a>'
))</p>
<p>image_processor = AutoImageProcessor.from_pretrained(checkpoint)
&lt;/tr&gt;&lt;/table&gt;
</code></pre></p>
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a href="https://github.com/huggingface/transformers/commit/6bc0fbcfa7acb6ac4937e7456a76c2f7975fefec"><code>6bc0fbc</code></a> [WIP] Emu3: add model (<a href="https://redirect.github.com/huggingface/transformers/issues/33770">#33770</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/59e28c30fa3a91213f569bccef73f082afa8c656"><code>59e28c3</code></a> Fix flex_attention in training mode (<a href="https://redirect.github.com/huggingface/transformers/issues/35605">#35605</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/7cf6230e25078742b21907ae49d1542747606457"><code>7cf6230</code></a> push a fix for now</li>
<li><a href="https://github.com/huggingface/transformers/commit/d6f446ffa79811d35484d445bc5c7932e8a536d6"><code>d6f446f</code></a> when filtering we can't use the convert script as we removed them</li>
<li><a href="https://github.com/huggingface/transformers/commit/8ce1e9578af6151e4192d59c345e2ad86ee789d4"><code>8ce1e95</code></a> [test-all]</li>
<li><a href="https://github.com/huggingface/transformers/commit/af2d7caff393cf8881396b73d92d0595b6a3b2ae"><code>af2d7ca</code></a> Add Moonshine  (<a href="https://redirect.github.com/huggingface/transformers/issues/34784">#34784</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/42b8e7916b6b6dff5cb77252286db1aa07b7b41e"><code>42b8e79</code></a> ModernBert: reuse GemmaRotaryEmbedding via modular + Integration tests (<a href="https://redirect.github.com/huggingface/transformers/issues/35459">#35459</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/e39c9f7a78fa2960a7045e8fc5a2d96b5d7eebf1"><code>e39c9f7</code></a> v4.48-release</li>
<li><a href="https://github.com/huggingface/transformers/commit/8de7b1ba8d126a6fc9f9bcc3173a71b46f0c3601"><code>8de7b1b</code></a> Add flex_attn to diffllama (<a href="https://redirect.github.com/huggingface/transformers/issues/35601">#35601</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/1e3ddcb2d0380d0d909a44edc217dff68956ec5e"><code>1e3ddcb</code></a> ModernBERT bug fixes (<a href="https://redirect.github.com/huggingface/transformers/issues/35404">#35404</a>)</li>
<li>Additional commits viewable in <a href="https://github.com/huggingface/transformers/compare/v4.38.0...v4.48.0">compare view</a></li>
</ul>
</details>
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