Bump transformers from 4.30.0 to 4.36.0 in /services/worker
Bumps [transformers](https://github.com/huggingface/transformers) from 4.30.0 to 4.36.0.
<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>v4.36: Mixtral, Llava/BakLlava, SeamlessM4T v2, AMD ROCm, F.sdpa wide-spread support</h2>
<h2>New model additions</h2>
<h3>Mixtral</h3>
<p>Mixtral is the new open-source model from Mistral AI announced by the blogpost <a href="https://mistral.ai/news/mixtral-of-experts/">Mixtral of Experts</a>. The model has been proven to have comparable capabilities to Chat-GPT according to the benchmark results shared on the release blogpost.</p>
<!-- raw HTML omitted -->
<p>The architecture is a sparse Mixture of Experts with Top-2 routing strategy, similar as <code>NllbMoe</code> architecture in transformers. You can use it through <code>AutoModelForCausalLM</code> interface:</p>
<pre lang="py"><code>&gt;&gt;&gt; import torch
&gt;&gt;&gt; from transformers import AutoModelForCausalLM, AutoTokenizer
<p>&gt;&gt;&gt; model = AutoModelForCausalLM.from_pretrained(&quot;mistralai/Mixtral-8x7B&quot;, torch_dtype=torch.float16, device_map=&quot;auto&quot;)
&gt;&gt;&gt; tokenizer = AutoTokenizer.from_pretrained(&quot;mistralai/Mistral-8x7B&quot;)</p>
<p>&gt;&gt;&gt; prompt = &quot;My favourite condiment is&quot;</p>
<p>&gt;&gt;&gt; model_inputs = tokenizer([prompt], return_tensors=&quot;pt&quot;).to(device)
&gt;&gt;&gt; model.to(device)</p>
<p>&gt;&gt;&gt; generated_ids = model.generate(**model_inputs, max_new_tokens=100, do_sample=True)
&gt;&gt;&gt; tokenizer.batch_decode(generated_ids)[0]
</code></pre></p>
<p>The model is compatible with existing optimisation tools such Flash Attention 2, <code>bitsandbytes</code> and PEFT library. The checkpoints are release under <a href="https://huggingface.co/mistralai"><code>mistralai</code></a> organisation on the Hugging Face Hub.</p>
<h3>Llava / BakLlava</h3>
<p>Llava is an open-source chatbot trained by fine-tuning LlamA/Vicuna on GPT-generated multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture. In other words, it is an multi-modal version of LLMs fine-tuned for chat / instructions.</p>
<!-- raw HTML omitted -->
<p>The Llava model was proposed in <a href="https://arxiv.org/pdf/2310.03744">Improved Baselines with Visual Instruction Tuning</a> by Haotian Liu, Chunyuan Li, Yuheng Li and Yong Jae Lee.</p>
<ul>
<li>[<code>Llava</code>] Add Llava to transformers  by <a href="https://github.com/younesbelkada"><code>@​younesbelkada</code></a> in <a href="https://redirect.github.com/huggingface/transformers/issues/27662">#27662</a></li>
<li>[LLaVa] Some improvements by <a href="https://github.com/NielsRogge"><code>@​NielsRogge</code></a> in <a href="https://redirect.github.com/huggingface/transformers/issues/27895">#27895</a></li>
</ul>
<p>The integration also includes <a href="https://github.com/SkunkworksAI/BakLLaVA"><code>BakLlava</code></a> which is a Llava model trained with Mistral backbone.</p>
<p>The mode is compatible with <code>&quot;image-to-text&quot;</code> pipeline:</p>
<pre lang="py"><code>from transformers import pipeline
from PIL import Image    
import requests
<p>model_id = &quot;llava-hf/llava-1.5-7b-hf&quot;
&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/14666775a296a76c88e1aa686a9547f393d322e2"><code>1466677</code></a> Release: v4.36.0</li>
<li><a href="https://github.com/huggingface/transformers/commit/accccdd0087263a1e494e9c9ec30a43043ff3905"><code>accccdd</code></a> [<code>Add Mixtral</code>] Adds support for the Mixtral MoE (<a href="https://redirect.github.com/huggingface/transformers/issues/27942">#27942</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/0676d992a5c1f6107a611018494ec952613a4d7f"><code>0676d99</code></a> [<code>from_pretrained</code>] Make from_pretrained fast again (<a href="https://redirect.github.com/huggingface/transformers/issues/27709">#27709</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/9f18cc6df0b7e0d50f78b9e9fcb3aafa7b5160fe"><code>9f18cc6</code></a> Fix SDPA dispatch &amp; make SDPA CI compatible with torch&lt;2.1.1 (<a href="https://redirect.github.com/huggingface/transformers/issues/27940">#27940</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/7ea21f1f035d683cc39a0c0f4b2605175e1dcfdf"><code>7ea21f1</code></a> [LLaVa] Some improvements (<a href="https://redirect.github.com/huggingface/transformers/issues/27895">#27895</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/5e620a92cf7e6c312435db86ec55e13b75dece75"><code>5e620a9</code></a> Fix <code>SeamlessM4Tv2ModelIntegrationTest</code> (<a href="https://redirect.github.com/huggingface/transformers/issues/27911">#27911</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/e96c1de1913c307fddcb3e5881388a6dbb5b00b1"><code>e96c1de</code></a> Skip <code>UnivNetModelTest::test_multi_gpu_data_parallel_forward</code> (<a href="https://redirect.github.com/huggingface/transformers/issues/27912">#27912</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/8d8970efdd0e21b54f1c82dec21e8a5eeba609a1"><code>8d8970e</code></a> [BEiT] Fix test (<a href="https://redirect.github.com/huggingface/transformers/issues/27934">#27934</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/235be08569000a5361354f766972e653212bf0d3"><code>235be08</code></a> [DETA] fix backbone freeze/unfreeze function (<a href="https://redirect.github.com/huggingface/transformers/issues/27843">#27843</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/df5c5c62ae253055336f5bb0828ca8e3e15ab6bd"><code>df5c5c6</code></a> Fix typo (<a href="https://redirect.github.com/huggingface/transformers/issues/27918">#27918</a>)</li>
<li>Additional commits viewable in <a href="https://github.com/huggingface/transformers/compare/v4.30.0...v4.36.0">compare view</a></li>
</ul>
</details>
<br />


[![Dependabot compatibility score](https://dependabot-badges.githubapp.com/badges/compatibility_score?dependency-name=transformers&package-manager=pip&previous-version=4.30.0&new-version=4.36.0)](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)

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</details>
Bump transformers from 4.30.0 to 4.36.0 in /services/worker: Bumps [transformers](https://github.com/huggingface/transformers) from 4.30.0 to 4.36.0.
<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>v4.36: Mixtral, Llava/BakLlava, SeamlessM4T v2, AMD ROCm, F.sdpa wide-spread support</h2>
<h2>New model additions</h2>
<h3>Mixtral</h3>
<p>Mixtral is the new open-source model from Mistral AI announced by the blogpost <a href="https://mistral.ai/news/mixtral-of-experts/">Mixtral of Experts</a>. The model has been proven to have comparable capabilities to Chat-GPT according to the benchmark results shared on the release blogpost.</p>
<!-- raw HTML omitted -->
<p>The architecture is a sparse Mixture of Experts with Top-2 routing strategy, similar as <code>NllbMoe</code> architecture in transformers. You can use it through <code>AutoModelForCausalLM</code> interface:</p>
<pre lang="py"><code>&gt;&gt;&gt; import torch
&gt;&gt;&gt; from transformers import AutoModelForCausalLM, AutoTokenizer
<p>&gt;&gt;&gt; model = AutoModelForCausalLM.from_pretrained(&quot;mistralai/Mixtral-8x7B&quot;, torch_dtype=torch.float16, device_map=&quot;auto&quot;)
&gt;&gt;&gt; tokenizer = AutoTokenizer.from_pretrained(&quot;mistralai/Mistral-8x7B&quot;)</p>
<p>&gt;&gt;&gt; prompt = &quot;My favourite condiment is&quot;</p>
<p>&gt;&gt;&gt; model_inputs = tokenizer([prompt], return_tensors=&quot;pt&quot;).to(device)
&gt;&gt;&gt; model.to(device)</p>
<p>&gt;&gt;&gt; generated_ids = model.generate(**model_inputs, max_new_tokens=100, do_sample=True)
&gt;&gt;&gt; tokenizer.batch_decode(generated_ids)[0]
</code></pre></p>
<p>The model is compatible with existing optimisation tools such Flash Attention 2, <code>bitsandbytes</code> and PEFT library. The checkpoints are release under <a href="https://huggingface.co/mistralai"><code>mistralai</code></a> organisation on the Hugging Face Hub.</p>
<h3>Llava / BakLlava</h3>
<p>Llava is an open-source chatbot trained by fine-tuning LlamA/Vicuna on GPT-generated multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture. In other words, it is an multi-modal version of LLMs fine-tuned for chat / instructions.</p>
<!-- raw HTML omitted -->
<p>The Llava model was proposed in <a href="https://arxiv.org/pdf/2310.03744">Improved Baselines with Visual Instruction Tuning</a> by Haotian Liu, Chunyuan Li, Yuheng Li and Yong Jae Lee.</p>
<ul>
<li>[<code>Llava</code>] Add Llava to transformers  by <a href="https://github.com/younesbelkada"><code>@​younesbelkada</code></a> in <a href="https://redirect.github.com/huggingface/transformers/issues/27662">#27662</a></li>
<li>[LLaVa] Some improvements by <a href="https://github.com/NielsRogge"><code>@​NielsRogge</code></a> in <a href="https://redirect.github.com/huggingface/transformers/issues/27895">#27895</a></li>
</ul>
<p>The integration also includes <a href="https://github.com/SkunkworksAI/BakLLaVA"><code>BakLlava</code></a> which is a Llava model trained with Mistral backbone.</p>
<p>The mode is compatible with <code>&quot;image-to-text&quot;</code> pipeline:</p>
<pre lang="py"><code>from transformers import pipeline
from PIL import Image    
import requests
<p>model_id = &quot;llava-hf/llava-1.5-7b-hf&quot;
&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/14666775a296a76c88e1aa686a9547f393d322e2"><code>1466677</code></a> Release: v4.36.0</li>
<li><a href="https://github.com/huggingface/transformers/commit/accccdd0087263a1e494e9c9ec30a43043ff3905"><code>accccdd</code></a> [<code>Add Mixtral</code>] Adds support for the Mixtral MoE (<a href="https://redirect.github.com/huggingface/transformers/issues/27942">#27942</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/0676d992a5c1f6107a611018494ec952613a4d7f"><code>0676d99</code></a> [<code>from_pretrained</code>] Make from_pretrained fast again (<a href="https://redirect.github.com/huggingface/transformers/issues/27709">#27709</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/9f18cc6df0b7e0d50f78b9e9fcb3aafa7b5160fe"><code>9f18cc6</code></a> Fix SDPA dispatch &amp; make SDPA CI compatible with torch&lt;2.1.1 (<a href="https://redirect.github.com/huggingface/transformers/issues/27940">#27940</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/7ea21f1f035d683cc39a0c0f4b2605175e1dcfdf"><code>7ea21f1</code></a> [LLaVa] Some improvements (<a href="https://redirect.github.com/huggingface/transformers/issues/27895">#27895</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/5e620a92cf7e6c312435db86ec55e13b75dece75"><code>5e620a9</code></a> Fix <code>SeamlessM4Tv2ModelIntegrationTest</code> (<a href="https://redirect.github.com/huggingface/transformers/issues/27911">#27911</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/e96c1de1913c307fddcb3e5881388a6dbb5b00b1"><code>e96c1de</code></a> Skip <code>UnivNetModelTest::test_multi_gpu_data_parallel_forward</code> (<a href="https://redirect.github.com/huggingface/transformers/issues/27912">#27912</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/8d8970efdd0e21b54f1c82dec21e8a5eeba609a1"><code>8d8970e</code></a> [BEiT] Fix test (<a href="https://redirect.github.com/huggingface/transformers/issues/27934">#27934</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/235be08569000a5361354f766972e653212bf0d3"><code>235be08</code></a> [DETA] fix backbone freeze/unfreeze function (<a href="https://redirect.github.com/huggingface/transformers/issues/27843">#27843</a>)</li>
<li><a href="https://github.com/huggingface/transformers/commit/df5c5c62ae253055336f5bb0828ca8e3e15ab6bd"><code>df5c5c6</code></a> Fix typo (<a href="https://redirect.github.com/huggingface/transformers/issues/27918">#27918</a>)</li>
<li>Additional commits viewable in <a href="https://github.com/huggingface/transformers/compare/v4.30.0...v4.36.0">compare view</a></li>
</ul>
</details>
<br />


[![Dependabot compatibility score](https://dependabot-badges.githubapp.com/badges/compatibility_score?dependency-name=transformers&package-manager=pip&previous-version=4.30.0&new-version=4.36.0)](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)

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