Bump transformers from 3.5.1 to 4.38.0 in /examples/research_projects/deebert
Author: dependabot[bot]
Pull request: yes
Labels: name: dependencies

name: python

Bumps [transformers](https://github.com/huggingface/transformers) from 3.5.1 to 4.38.0.
<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>v4.38: Gemma, Depth Anything, Stable LM; Static Cache, HF Quantizer, AQLM</h2>
<h2>New model additions</h2>
<h3>💎 Gemma 💎</h3>
<p>Gemma is a new opensource Language Model series from Google AI that comes with a 2B and 7B variant. The release comes with the pre-trained and instruction fine-tuned versions and you can use them via <code>AutoModelForCausalLM</code>, <code>GemmaForCausalLM</code> or <code>pipeline</code> interface!</p>
<p>Read more about it in the Gemma release blogpost: <a href="https://hf.co/blog/gemma">https://hf.co/blog/gemma</a></p>
<pre lang="python"><code>from transformers import AutoTokenizer, AutoModelForCausalLM
<p>tokenizer = AutoTokenizer.from_pretrained(&quot;google/gemma-2b&quot;)
model = AutoModelForCausalLM.from_pretrained(&quot;google/gemma-2b&quot;, device_map=&quot;auto&quot;, torch_dtype=torch.float16)</p>
<p>input_text = &quot;Write me a poem about Machine Learning.&quot;
input_ids = tokenizer(input_text, return_tensors=&quot;pt&quot;).to(&quot;cuda&quot;)</p>
<p>outputs = model.generate(**input_ids)
</code></pre></p>
<p>You can use the model with Flash Attention, SDPA, Static cache and quantization API for further optimizations !</p>
<ul>
<li>Flash Attention 2</li>
</ul>
<pre lang="python"><code>from transformers import AutoTokenizer, AutoModelForCausalLM
<p>tokenizer = AutoTokenizer.from_pretrained(&quot;google/gemma-2b&quot;)</p>
<p>model = AutoModelForCausalLM.from_pretrained(
&quot;google/gemma-2b&quot;, device_map=&quot;auto&quot;, torch_dtype=torch.float16, attn_implementation=&quot;flash_attention_2&quot;
)</p>
<p>input_text = &quot;Write me a poem about Machine Learning.&quot;
input_ids = tokenizer(input_text, return_tensors=&quot;pt&quot;).to(&quot;cuda&quot;)</p>
<p>outputs = model.generate(**input_ids)
</code></pre></p>
<ul>
<li>bitsandbytes-4bit</li>
</ul>
<pre lang="python"><code>from transformers import AutoTokenizer, AutoModelForCausalLM
<p>tokenizer = AutoTokenizer.from_pretrained(&quot;google/gemma-2b&quot;)</p>
<p>model = AutoModelForCausalLM.from_pretrained(
&quot;google/gemma-2b&quot;, device_map=&quot;auto&quot;, load_in_4bit=True
)
&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/08ab54ada594f8f4cc1e458b1217bf8c53f04dd8"><code>08ab54a</code></a> [ <code>gemma</code>] Adds support for Gemma 💎 (<a href="https://redirect.github.com/huggingface/transformers/issues/29167">#29167</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/2de9314197a12e134f3fff2710f6d86e97b774a3"><code>2de9314</code></a> [<code>Maskformer</code>] safely get backbone config (<a href="https://redirect.github.com/huggingface/transformers/issues/29166">#29166</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/476957b5b471fe8a3be9968485118c67a739a044"><code>476957b</code></a> 🚨 Llama: update rope scaling to match static cache changes (<a href="https://redirect.github.com/huggingface/transformers/issues/29143">#29143</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/7a4bec6e8f6f81f47228092b9f6b9b7e2b55ebe7"><code>7a4bec6</code></a> Release: 4.38.0</li>
<li><a href="https://github.com/huggingface/transformers/commit/ee3af60be0d21044692211d97dfd858aa3e4b418"><code>ee3af60</code></a> Add support for fine-tuning CLIP-like models using contrastive-image-text exa...</li>
<li><a href="https://github.com/huggingface/transformers/commit/0996a10077219de0556281511fc02f3ab68002d5"><code>0996a10</code></a> Revert low cpu mem tie weights (<a href="https://redirect.github.com/huggingface/transformers/issues/29135">#29135</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/15cfe38942e4012f5476e7f45dfacf26791b0ccc"><code>15cfe38</code></a> [<code>Core tokenization</code>]  <code>add_dummy_prefix_space</code> option to help with latest is...</li>
<li><a href="https://github.com/huggingface/transformers/commit/efdd436663436e78d8ad3213d11325d86578db95"><code>efdd436</code></a> FIX [<code>PEFT</code> / <code>Trainer</code> ] Handle better peft + quantized compiled models (<a href="https://redirect.github.com/huggingface/transformers/issues/29">#29</a>...</li>
<li><a href="https://github.com/huggingface/transformers/commit/5e95dcabe1d3d522a8bc5a45990c53d9d4e9f2eb"><code>5e95dca</code></a> [<code>cuda kernels</code>] only compile them when initializing (<a href="https://redirect.github.com/huggingface/transformers/issues/29133">#29133</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/a7755d24096306c84a3557394b54a95db7a0f76f"><code>a7755d2</code></a> Generate: unset GenerationConfig parameters do not raise warning (<a href="https://redirect.github.com/huggingface/transformers/issues/29119">#29119</a>)</li>
<li>Additional commits viewable in <a href="https://github.com/huggingface/transformers/compare/v3.5.1...v4.38.0">compare view</a></li>
</ul>
</details>
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