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| <link rel="modulepreload" href="/docs/optimum.neuron/pr_1097/en/_app/immutable/chunks/CodeBlock.2d00672f.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{"title":"IP-Adapter","local":"ip-adapter","sections":[{"title":"Overview","local":"overview","sections":[],"depth":2},{"title":"Export to Neuron","local":"export-to-neuron","sections":[{"title":"Option 1: CLI","local":"option-1-cli","sections":[],"depth":3},{"title":"Option 2: Python API","local":"option-2-python-api","sections":[],"depth":3}],"depth":2},{"title":"Text-to-Image","local":"text-to-image","sections":[],"depth":2}],"depth":1}"><!-- HEAD_svelte-u9bgzb_END --> <p></p> <div class="items-center shrink-0 min-w-[100px] max-sm:min-w-[50px] justify-end ml-auto flex" style="float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"><div class="inline-flex rounded-md max-sm:rounded-sm"><button class="inline-flex items-center gap-1 h-7 max-sm:h-7 px-2 max-sm:px-1.5 text-sm font-medium text-gray-800 border border-r-0 rounded-l-md max-sm:rounded-l-sm border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-live="polite"><span class="inline-flex items-center justify-center rounded-md p-0.5 max-sm:p-0 hover:text-gray-800 dark:hover:text-gray-200"><svg class="sm:size-3.5 size-3" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg></span> <span>Copy page</span></button> <button class="inline-flex items-center justify-center w-6 max-sm:w-5 h-7 max-sm:h-7 disabled:pointer-events-none text-sm text-gray-500 hover:text-gray-700 dark:hover:text-white rounded-r-md max-sm:rounded-r-sm border border-l transition border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-haspopup="menu" aria-expanded="false" aria-label="Open copy menu"><svg class="transition-transform text-gray-400 overflow-visible sm:size-3.5 size-3 rotate-0" width="1em" height="1em" viewBox="0 0 12 7" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M1 1L6 6L11 1" stroke="currentColor"></path></svg></button></div> </div> <h1 class="relative group"><a id="ip-adapter" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#ip-adapter"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>IP-Adapter</span></h1> <h2 class="relative group"><a id="overview" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#overview"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Overview</span></h2> <p data-svelte-h="svelte-rd9njz"><a href="https://hf.co/papers/2308.06721" rel="nofollow">IP-Adapter</a> is an image prompt adapter that can be plugged into diffusion models to enable image prompting without any changes to the underlying model. Furthermore, this adapter can be reused with other models finetuned from the same base model and it can be combined with other adapters like <a href="../using-diffusers/controlnet">ControlNet</a>. The key idea behind IP-Adapter is the <em>decoupled cross-attention</em> mechanism which adds a separate cross-attention layer just for image features instead of using the same cross-attention layer for both text and image features. This allows the model to learn more image-specific features.</p> <p data-svelte-h="svelte-1g87d8z">🤗 <code>Optimum</code> extends <code>Diffusers</code> to support inference on the second generation of Neuron devices(powering Trainium and Inferentia 2). It aims at inheriting the ease of Diffusers on Neuron.</p> <h2 class="relative group"><a id="export-to-neuron" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#export-to-neuron"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Export to Neuron</span></h2> <p data-svelte-h="svelte-mxgu63">To deploy models, you will need to compile them to TorchScript optimized for AWS Neuron.</p> <p data-svelte-h="svelte-15y00oa">You can either compile and export a Stable Diffusion Checkpoint via CLI or <code>NeuronStableDiffusionPipeline</code> class.</p> <h3 class="relative group"><a id="option-1-cli" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#option-1-cli"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Option 1: CLI</span></h3> <p data-svelte-h="svelte-ktaj8q">Here is an example of exporting stable diffusion components with <code>Optimum</code> CLI:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START -->optimum-cli <span class="hljs-built_in">export</span> neuron --model stable-diffusion-v1-5/stable-diffusion-v1-5 | |
| --ip_adapter_id h94/IP-Adapter | |
| --ip_adapter_subfolder models | |
| --ip_adapter_weight_name ip-adapter-full-face_sd15.bin | |
| --ip_adapter_scale 0.5 | |
| --batch_size 1 --height 512 --width 512 --num_images_per_prompt 1 | |
| --auto_cast matmul --auto_cast_type bf16 ip_adapter_neuron/<!-- HTML_TAG_END --></pre></div> <blockquote class="tip" data-svelte-h="svelte-6gfoqi"><p>We recommend using a <code>inf2.8xlarge</code> or a larger instance for the model compilation. You will also be able to compile the model with the Optimum CLI on a CPU-only instance (needs ~35 GB memory), and then run the pre-compiled model on <code>inf2.xlarge</code> to reduce the expenses. In this case, don’t forget to disable validation of inference by adding the <code>--disable-validation</code> argument.</p></blockquote> <h3 class="relative group"><a id="option-2-python-api" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#option-2-python-api"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Option 2: Python API</span></h3> <p data-svelte-h="svelte-1bahy14">Here is an example of exporting stable diffusion components with <code>NeuronStableDiffusionPipeline</code>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionPipeline | |
| model_id = <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-v1-5"</span> | |
| compiler_args = {<span class="hljs-string">"auto_cast"</span>: <span class="hljs-string">"matmul"</span>, <span class="hljs-string">"auto_cast_type"</span>: <span class="hljs-string">"bf16"</span>} | |
| input_shapes = {<span class="hljs-string">"batch_size"</span>: <span class="hljs-number">1</span>, <span class="hljs-string">"height"</span>: <span class="hljs-number">512</span>, <span class="hljs-string">"width"</span>: <span class="hljs-number">512</span>} | |
| stable_diffusion = NeuronStableDiffusionPipeline.from_pretrained( | |
| model_id, | |
| export=<span class="hljs-literal">True</span>, | |
| ip_adapter_id=<span class="hljs-string">"h94/IP-Adapter"</span>, | |
| ip_adapter_subfolder=<span class="hljs-string">"models"</span>, | |
| ip_adapter_weight_name=<span class="hljs-string">"ip-adapter-full-face_sd15.bin"</span>, | |
| ip_adapter_scale=<span class="hljs-number">0.5</span>, | |
| **compiler_args, | |
| **input_shapes, | |
| ) | |
| <span class="hljs-comment"># Save locally or upload to the HuggingFace Hub</span> | |
| save_directory = <span class="hljs-string">"ip_adapter_neuron/"</span> | |
| stable_diffusion.save_pretrained(save_directory)<!-- HTML_TAG_END --></pre></div> <h2 class="relative group"><a id="text-to-image" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#text-to-image"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Text-to-Image</span></h2> <ul data-svelte-h="svelte-1erevtl"><li>With <code>ip_adapter_image</code> as input</li></ul> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronStableDiffusionPipeline | |
| model_id = <span class="hljs-string">"stable-diffusion-v1-5/stable-diffusion-v1-5"</span> | |
| compiler_args = {<span class="hljs-string">"auto_cast"</span>: <span class="hljs-string">"matmul"</span>, <span class="hljs-string">"auto_cast_type"</span>: <span class="hljs-string">"bf16"</span>} | |
| input_shapes = {<span class="hljs-string">"batch_size"</span>: <span class="hljs-number">1</span>, <span class="hljs-string">"height"</span>: <span class="hljs-number">512</span>, <span class="hljs-string">"width"</span>: <span class="hljs-number">512</span>} | |
| stable_diffusion = NeuronStableDiffusionPipeline.from_pretrained( | |
| model_id, | |
| export=<span class="hljs-literal">True</span>, | |
| ip_adapter_id=<span class="hljs-string">"h94/IP-Adapter"</span>, | |
| ip_adapter_subfolder=<span class="hljs-string">"models"</span>, | |
| ip_adapter_weight_name=<span class="hljs-string">"ip-adapter-full-face_sd15.bin"</span>, | |
| ip_adapter_scale=<span class="hljs-number">0.5</span>, | |
| **compiler_args, | |
| **input_shapes, | |
| ) | |
| <span class="hljs-comment"># Save locally or upload to the HuggingFace Hub</span> | |
| save_directory = <span class="hljs-string">"ip_adapter_neuron/"</span> | |
| stable_diffusion.save_pretrained(save_directory)<!-- HTML_TAG_END --></pre></div> <ul data-svelte-h="svelte-1mmoknp"><li>With <code>ip_adapter_image_embeds</code> as input (encode the image first)</li></ul> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START -->image_embeds = stable_diffusion.prepare_ip_adapter_image_embeds( | |
| ip_adapter_image=image, | |
| ip_adapter_image_embeds=<span class="hljs-literal">None</span>, | |
| device=<span class="hljs-literal">None</span>, | |
| num_images_per_prompt=<span class="hljs-number">1</span>, | |
| do_classifier_free_guidance=<span class="hljs-literal">True</span>, | |
| ) | |
| torch.save(image_embeds, <span class="hljs-string">"image_embeds.ipadpt"</span>) | |
| image_embeds = torch.load(<span class="hljs-string">"image_embeds.ipadpt"</span>) | |
| images = stable_diffusion( | |
| prompt=<span class="hljs-string">"a polar bear sitting in a chair drinking a milkshake"</span>, | |
| ip_adapter_image_embeds=image_embeds, | |
| negative_prompt=<span class="hljs-string">"deformed, ugly, wrong proportion, low res, bad anatomy, worst quality, low quality"</span>, | |
| num_inference_steps=<span class="hljs-number">100</span>, | |
| generator=generator, | |
| ).images[<span class="hljs-number">0</span>] | |
| image.save(<span class="hljs-string">"polar_bear.png"</span>)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1wos5lv">Are there any other diffusion features that you want us to support in 🤗<code>Optimum-neuron</code>? Please file an issue to <a href="https://github.com/huggingface/optimum-neuron" rel="nofollow"><code>Optimum-neuron</code> Github repo</a> or discuss with us on <a href="https://discuss.huggingface.co/c/optimum/" rel="nofollow">HuggingFace’s community forum</a>, cheers 🤗 !</p> <p></p> | |
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