optimum-neuron/pr_1109/en/_app/immutable/nodes/52.d5b2d2fe.js

import{s as V,n as G,o as J}from"../chunks/scheduler.56725da7.js";import{S as K,i as N,e as s,s as r,c as H,h as X,a as l,d as e,b as a,f as I,g as q,j as w,k as U,v as x,l as Z,m as i,n as j,t as A,o as F,p as R}from"../chunks/index.18a26576.js";import{C as tt}from"../chunks/CopyLLMTxtMenu.a1f2bcd7.js";import{H as O}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.9f98faf7.js";function nt(E){let p,v,b,k,m,_,d,L,g,Y="Learn how to run and fine-tune models for optimal performance with AWS Trainium.",$,o,W=`<a href="./finetune_llama" style="text-decoration: none !important; color: inherit !important; display: block !important;"><div style="border-radius: 8px !important; background-color: white !important; box-shadow: 0 2px 8px rgba(0,0,0,0.1) !important; transition: all 0.3s ease-in-out !important; cursor: pointer !important; display: flex !important; flex-direction: column !important; height: 280px !important; width: 100% !important; border: none !important;" onmouseover="this.style.transform=&#39;translateY(-4px)&#39;; this.style.boxShadow=&#39;0 8px 24px rgba(0,0,0,0.15)&#39;; this.querySelector(&#39;.card-content&#39;).style.backgroundPosition=&#39;0% 0&#39;" onmouseout="this.style.transform=&#39;translateY(0)&#39;; this.style.boxShadow=&#39;0 2px 8px rgba(0,0,0,0.1)&#39;; this.querySelector(&#39;.card-content&#39;).style.backgroundPosition=&#39;100% 0&#39;"><div style="height: 180px !important; width: 100% !important; background: linear-gradient(135deg, #FF6B35 0%, #F7931E 100%) !important; display: flex !important; align-items: center !important; justify-content: center !important; position: relative !important; border: none !important; margin: 0 !important; padding: 0 !important; border-radius: 8px 8px 0 0 !important; overflow: hidden !important;"><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/optimum/neuron/training_tutorials/llama-logo.png" alt="Llama 3" style="width: 100% !important; height: 100% !important; object-fit: cover !important; border: none !important; border-radius: 8px 8px 0 0 !important;" onerror="this.outerHTML=&#39;&lt;div style=&#39;color: white; font-size: 48px; font-weight: bold; z-index: 10;
position: relative;&#39;&gt;🦙&lt;/div&gt;&#39;"/></div> <div class="card-content" style="padding: 20px !important; background: white !important; background-image: linear-gradient(90deg, transparent 0%, #f8f9fa 50%, #e9ecef 100%) !important; background-size: 200% 100% !important; background-position: 100% 0 !important; transition: background-position 0.4s ease-out !important; width: 100% !important; box-sizing: border-box !important; flex: 1 !important; border: none !important; margin: 0 !important; border-radius: 0 0 8px 8px !important;"><h3 style="margin: 0 0 8px 0 !important; font-size: 18px !important; font-weight: 600 !important; color: #24292e !important;">Llama 3.1</h3> <p style="margin: 0 !important; font-size: 14px !important; color: #586069 !important; line-height: 1.4 !important;">Instruction Fine-tuning of Llama 3.1 8B with LoRA on the Dolly dataset</p></div></div></a> <a href="./finetune_qwen3" style="text-decoration: none !important; color: inherit !important; display: block !important;"><div style="border-radius: 8px !important; background-color: white !important; box-shadow: 0 2px 8px rgba(0,0,0,0.1) !important; transition: all 0.3s ease-in-out !important; cursor: pointer !important; display: flex !important; flex-direction: column !important; height: 280px !important; width: 100% !important; border: none !important;" onmouseover="this.style.transform=&#39;translateY(-4px)&#39;; this.style.boxShadow=&#39;0 8px 24px rgba(0,0,0,0.15)&#39;; this.querySelector(&#39;.card-content&#39;).style.backgroundPosition=&#39;0% 0&#39;" onmouseout="this.style.transform=&#39;translateY(0)&#39;; this.style.boxShadow=&#39;0 2px 8px rgba(0,0,0,0.1)&#39;;
this.querySelector(&#39;.card-content&#39;).style.backgroundPosition=&#39;100% 0&#39;"><div style="height: 180px !important; width: 100% !important; background: linear-gradient(135deg, #faf5ff 0%, #f3e8ff 100%) !important; display: flex !important; align-items: center !important; justify-content: center !important; position: relative !important; border: none !important; margin: 0 !important; padding: 0 !important; border-radius: 8px 8px 0 0 !important; overflow: hidden !important;"><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/optimum/neuron/training_tutorials/qwen3-logo.png" alt="Qwen3" style="width: 100% !important; height: 100% !important; object-fit: cover !important; border: none !important; border-radius: 8px 8px 0 0 !important;" onerror="this.outerHTML=&#39;&lt;div style=&#39;color: white; font-size: 48px;
font-weight: bold; z-index: 10; position: relative;&#39;&gt;🔷&lt;/div&gt;&#39;"/></div> <div class="card-content" style="padding: 20px !important; background: white !important; background-image: linear-gradient(90deg, transparent 0%, #f8f9fa 50%, #e9ecef 100%) !important; background-size: 200% 100% !important; background-position: 100% 0 !important; transition: background-position 0.4s ease-out !important; width: 100% !important; box-sizing: border-box !important; flex: 1 !important; border: none !important; margin: 0 !important; border-radius: 0 0 8px 8px !important;"><h3 style="margin: 0 0 8px 0 !important; font-size: 18px !important; font-weight: 600 !important; color: #24292e !important;">Qwen3</h3> <p style="margin: 0 !important; font-size: 14px !important; color: #586069 !important; line-height: 1.4 !important;">Fine-tune Qwen3 8B with LoRA on the Simple Recipes dataset</p></div></div></a> <a href="./pretraining_hyperpod_llm" style="text-decoration: none !important; color: inherit !important; display: block !important;"><div style="border-radius: 8px !important; background-color: white !important; box-shadow: 0 2px 8px rgba(0,0,0,0.1) !important; transition: all 0.3s ease-in-out !important; cursor: pointer !important; display: flex !important; flex-direction: column !important; height: 280px !important; width: 100% !important; border: none !important;" onmouseover="this.style.transform=&#39;translateY(-4px)&#39;; this.style.boxShadow=&#39;0 8px 24px rgba(0,0,0,0.15)&#39;; this.querySelector(&#39;.card-content&#39;).style.backgroundPosition=&#39;0% 0&#39;" onmouseout="this.style.transform=&#39;translateY(0)&#39;; this.style.boxShadow=&#39;0 2px 8px rgba(0,0,0,0.1)&#39;;
this.querySelector(&#39;.card-content&#39;).style.backgroundPosition=&#39;100% 0&#39;"><div style="height: 180px !important; width: 100% !important; background: linear-gradient(135deg, #059669 0%, #0891b2 100%) !important; display: flex !important; align-items: center !important; justify-content: center !important; position: relative !important; border: none !important; margin: 0 !important; padding: 0 !important; border-radius: 8px 8px 0 0 !important; overflow: hidden !important;"><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/optimum/neuron/training_tutorials/sagemaker-logo.png" alt="SageMaker Hyperpod" style="width: 100% !important; height: 100% !important; object-fit: cover !important; border: none !important; border-radius: 8px 8px 0 0 !important;" onerror="this.outerHTML=&#39;&lt;div style=&#39;color: white; font-size: 28px;
font-weight: bold; text-align: center; z-index: 10; position: relative;&#39;&gt;☁️&lt;br/&gt;SageMaker&lt;/div&gt;&#39;"/></div> <div class="card-content" style="padding: 20px !important; background: white !important; background-image: linear-gradient(90deg, transparent 0%, #f8f9fa 50%, #e9ecef 100%) !important; background-size: 200% 100% !important; background-position: 100% 0 !important; transition: background-position 0.4s ease-out !important; width: 100% !important; box-sizing: border-box !important; flex: 1 !important; border: none !important; margin: 0 !important; border-radius: 0 0 8px 8px !important;"><h3 style="margin: 0 0 8px 0 !important; font-size: 18px !important; font-weight: 600 !important; color: #24292e !important;">Llama 3.2 on SageMaker</h3> <p style="margin: 0 !important; font-size: 14px !important; color: #586069 !important; line-height: 1.4 !important;">Continuous Pretraining of Llama 3.2 1B on SageMaker Hyperpod</p></div></div></a>`,S,u,z,c,B="These tutorials will guide you through the complete process of fine-tuning large language models on AWS Trainium:",M,h,D="<li><strong>📊 Data Preparation</strong>: Load and preprocess datasets for supervised fine-tuning</li> <li><strong>🔧 Model Configuration</strong>: Set up LoRA adapters and distributed training parameters</li> <li><strong>⚡ Training Optimization</strong>: Leverage tensor parallelism, gradient checkpointing, and mixed precision</li> <li><strong>💾 Checkpoint Management</strong>: Consolidate and merge model checkpoints for deployment</li> <li><strong>🚀 Model Deployment</strong>: Export and test your fine-tuned models for inference</li>",T,f,Q="Choose the tutorial that best fits your use case and start fine-tuning your LLMs on AWS Trainium today!",C,y,P;return m=new tt({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),d=new O({props:{title:"🚀  Tutorials: How To Fine-tune & Run LLMs",local:"-tutorials-how-to-fine-tune--run-llms",headingTag:"h1"}}),u=new O({props:{title:"What you’ll learn",local:"what-youll-learn",headingTag:"h2"}}),{c(){p=s("meta"),v=r(),b=s("p"),k=r(),H(m.$$.fragment),_=r(),H(d.$$.fragment),L=r(),g=s("p"),g.textContent=Y,$=r(),o=s("div"),o.innerHTML=W,S=r(),H(u.$$.fragment),z=r(),c=s("p"),c.textContent=B,M=r(),h=s("ul"),h.innerHTML=D,T=r(),f=s("p"),f.textContent=Q,C=r(),y=s("p"),this.h()},l(t){const n=X("svelte-u9bgzb",document.head);p=l(n,"META",{name:!0,content:!0}),n.forEach(e),v=a(t),b=l(t,"P",{}),I(b).forEach(e),k=a(t),q(m.$$.fragment,t),_=a(t),q(d.$$.fragment,t),L=a(t),g=l(t,"P",{"data-svelte-h":!0}),w(g)!=="svelte-1qf0ci3"&&(g.textContent=Y),$=a(t),o=l(t,"DIV",{style:!0,"data-svelte-h":!0}),w(o)!=="svelte-12hlu8q"&&(o.innerHTML=W),S=a(t),q(u.$$.fragment,t),z=a(t),c=l(t,"P",{"data-svelte-h":!0}),w(c)!=="svelte-1wtbpo2"&&(c.textContent=B),M=a(t),h=l(t,"UL",{"data-svelte-h":!0}),w(h)!=="svelte-1zufjx"&&(h.innerHTML=D),T=a(t),f=l(t,"P",{"data-svelte-h":!0}),w(f)!=="svelte-11li9sy"&&(f.textContent=Q),C=a(t),y=l(t,"P",{}),I(y).forEach(e),this.h()},h(){U(p,"name","hf:doc:metadata"),U(p,"content",et),x(o,"display","grid",1),x(o,"grid-template-columns","repeat(auto-fit, minmax(400px, 1fr))",1),x(o,"gap","24px",1),x(o,"margin","32px -32px",1),x(o,"padding","0 32px",1),x(o,"max-width","none",1),x(o,"width","calc(100% + 64px)",1)},m(t,n){Z(document.head,p),i(t,v,n),i(t,b,n),i(t,k,n),j(m,t,n),i(t,_,n),j(d,t,n),i(t,L,n),i(t,g,n),i(t,$,n),i(t,o,n),i(t,S,n),j(u,t,n),i(t,z,n),i(t,c,n),i(t,M,n),i(t,h,n),i(t,T,n),i(t,f,n),i(t,C,n),i(t,y,n),P=!0},p:G,i(t){P||(A(m.$$.fragment,t),A(d.$$.fragment,t),A(u.$$.fragment,t),P=!0)},o(t){F(m.$$.fragment,t),F(d.$$.fragment,t),F(u.$$.fragment,t),P=!1},d(t){t&&(e(v),e(b),e(k),e(_),e(L),e(g),e($),e(o),e(S),e(z),e(c),e(M),e(h),e(T),e(f),e(C),e(y)),e(p),R(m,t),R(d,t),R(u,t)}}}const et='{"title":"🚀  Tutorials: How To Fine-tune & Run LLMs","local":"-tutorials-how-to-fine-tune--run-llms","sections":[{"title":"What you’ll learn","local":"what-youll-learn","sections":[],"depth":2}],"depth":1}';function it(E){return J(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class st extends K{constructor(p){super(),N(this,p,it,nt,V,{})}}export{st as component};