Buckets:
| import{s as fe,n as he,o as ce}from"../chunks/scheduler.b108d059.js";import{S as de,i as Ce,g as a,s as n,r as s,A as xe,h as r,f as l,c as i,j as ue,u as m,x as c,k as pe,y as we,a as o,v as u,d as p,t as f,w as h}from"../chunks/index.008de539.js";import{H as d,E as Ge}from"../chunks/EditOnGithub.d1c48e3d.js";function $e(le){let g,P,H,V,C,F,x,oe="Learn how to use Hugging Face in Google Cloud by reading our blog posts, presentations, Google documentation and examples below.",U,w,K,G,ne='<li><a href="https://huggingface.co/blog/gcp-partnership" rel="nofollow">Hugging Face and Google partner for open AI collaboration</a></li> <li><a href="https://huggingface.co/blog/tpu-inference-endpoints-spaces" rel="nofollow">Google Cloud TPUs made available to Hugging Face users</a></li> <li><a href="https://huggingface.co/blog/google-cloud-model-garden" rel="nofollow">Making thousands of open LLMs bloom in the Vertex AI Model Garden</a></li> <li><a href="https://huggingface.co/blog/llama31-on-vertex-ai" rel="nofollow">Deploy Meta Llama 3.1 405B on Google Cloud Vertex AI</a></li>',R,$,S,v,ie='<li><a href="https://rsvp.withgoogle.com/events/gemma-dev-day_2024tokyo/sessions/hugging-face-transformers" rel="nofollow">Gemma Developer Day in Tokyo | Unleashing Gemma in production with Hugging Face Text Generation Inference (TGI)</a></li>',q,b,j,L,ae='<li><a href="https://cloud.google.com/deep-learning-containers/docs/choosing-container#hugging-face" rel="nofollow">Google Cloud Hugging Face Deep Learning Containers</a></li> <li><a href="https://console.cloud.google.com/artifacts/docker/deeplearning-platform-release/us/gcr.io" rel="nofollow">Google Cloud public Artifact Registry for DLCs</a></li> <li><a href="https://cloud.google.com/kubernetes-engine/docs/tutorials/serve-gemma-gpu-tgi" rel="nofollow">Serve Gemma open models using GPUs on GKE with Hugging Face TGI</a></li> <li><a href="https://cloud.google.com/vertex-ai/generative-ai/docs/open-models/use-hugging-face-models" rel="nofollow">Generative AI on Vertex - Use Hugging Face text generation models</a></li>',z,T,O,y,re='<li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples" rel="nofollow">All examples</a></li>',Q,D,X,I,ge='<li><p>Inference</p> <ul><li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/deploy-bert-on-vertex-ai" rel="nofollow">Deploy BERT Models with PyTorch Inference DLC on Vertex AI</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/deploy-embedding-on-vertex-ai" rel="nofollow">Deploy Embedding Models with TEI DLC on Vertex AI</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/deploy-flux-on-vertex-ai" rel="nofollow">Deploy FLUX with PyTorch Inference DLC on Vertex AI</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/deploy-gemma-from-gcs-on-vertex-ai" rel="nofollow">Deploy Gemma 7B with TGI DLC from GCS on Vertex AI</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/deploy-gemma-on-vertex-ai" rel="nofollow">Deploy Gemma 7B with TGI DLC on Vertex AI</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/deploy-llama-vision-on-vertex-ai" rel="nofollow">Deploy Llama 3.2 11B Vision with TGI DLC on Vertex AI</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/deploy-llama-3-1-405b-on-vertex-ai" rel="nofollow">Deploy Meta Llama 3.1 405B with TGI DLC on Vertex AI</a></li></ul></li> <li><p>Training</p> <ul><li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/trl-lora-sft-fine-tuning-on-vertex-ai" rel="nofollow">Fine-tune Gemma 2B with PyTorch Training DLC using SFT + LoRA on Vertex AI</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/trl-full-sft-fine-tuning-on-vertex-ai" rel="nofollow">Fine-tune Mistral 7B v0.3 with PyTorch Training DLC using SFT on Vertex AI</a></li></ul></li> <li><p>Evaluation</p> <ul><li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/vertex-ai/notebooks/evaluate-llms-with-vertex-ai" rel="nofollow">Evaluate open LLMs with Vertex AI and Gemini</a></li></ul></li>',J,k,N,E,se='<li><p>Inference</p> <ul><li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/gke/tei-from-gcs-deployment" rel="nofollow">Deploy BGE Base v1.5 with TEI DLC from GCS on GKE</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/gke/tgi-multi-lora-deployment" rel="nofollow">Deploy Gemma2 with multiple LoRA adapters with TGI DLC on GKE</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/gke/tgi-llama-405b-deployment" rel="nofollow">Deploy Llama 3.1 405B with TGI DLC on GKE</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/gke/tgi-llama-vision-deployment" rel="nofollow">Deploy Llama 3.2 11B Vision with TGI DLC on GKE</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/gke/tgi-deployment" rel="nofollow">Deploy Meta Llama 3 8B with TGI DLC on GKE</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/gke/tgi-from-gcs-deployment" rel="nofollow">Deploy Qwen2 7B with TGI DLC from GCS on GKE</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/gke/tei-deployment" rel="nofollow">Deploy Snowflake’s Arctic Embed with TEI DLC on GKE</a></li></ul></li> <li><p>Training</p> <ul><li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/gke/trl-full-fine-tuning" rel="nofollow">Fine-tune Gemma 2B with PyTorch Training DLC using SFT on GKE</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/gke/trl-lora-fine-tuning" rel="nofollow">Fine-tune Mistral 7B v0.3 with PyTorch Training DLC using SFT + LoRA on GKE</a></li></ul></li>',W,M,Y,_,me='<li><p>Inference</p> <ul><li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/cloud-run/deploy-gemma-2-on-cloud-run" rel="nofollow">Deploy Gemma2 9B with TGI DLC on Cloud Run</a></li> <li><a href="https://github.com/huggingface/Google-Cloud-Containers/tree/main/examples/cloud-run/deploy-llama-3-1-on-cloud-run" rel="nofollow">Deploy Llama 3.1 8B with TGI DLC on Cloud Run</a></li></ul></li>',Z,A,ee,B,te;return C=new d({props:{title:"📄 Other Resources",local:"-other-resources",headingTag:"h1"}}),w=new d({props:{title:"Blog posts",local:"blog-posts",headingTag:"h2"}}),$=new d({props:{title:"Presentations",local:"presentations",headingTag:"h2"}}),b=new d({props:{title:"Google Documentation",local:"google-documentation",headingTag:"h2"}}),T=new d({props:{title:"Examples",local:"examples",headingTag:"h2"}}),D=new d({props:{title:"Vertex AI",local:"vertex-ai",headingTag:"h3"}}),k=new d({props:{title:"GKE",local:"gke",headingTag:"h3"}}),M=new d({props:{title:"(Preview) Cloud Run",local:"preview-cloud-run",headingTag:"h3"}}),A=new Ge({props:{source:"https://github.com/huggingface/Google-Cloud-Containers/blob/main/docs/source/resources.mdx"}}),{c(){g=a("meta"),P=n(),H=a("p"),V=n(),s(C.$$.fragment),F=n(),x=a("p"),x.textContent=oe,U=n(),s(w.$$.fragment),K=n(),G=a("ul"),G.innerHTML=ne,R=n(),s($.$$.fragment),S=n(),v=a("ul"),v.innerHTML=ie,q=n(),s(b.$$.fragment),j=n(),L=a("ul"),L.innerHTML=ae,z=n(),s(T.$$.fragment),O=n(),y=a("ul"),y.innerHTML=re,Q=n(),s(D.$$.fragment),X=n(),I=a("ul"),I.innerHTML=ge,J=n(),s(k.$$.fragment),N=n(),E=a("ul"),E.innerHTML=se,W=n(),s(M.$$.fragment),Y=n(),_=a("ul"),_.innerHTML=me,Z=n(),s(A.$$.fragment),ee=n(),B=a("p"),this.h()},l(e){const t=xe("svelte-u9bgzb",document.head);g=r(t,"META",{name:!0,content:!0}),t.forEach(l),P=i(e),H=r(e,"P",{}),ue(H).forEach(l),V=i(e),m(C.$$.fragment,e),F=i(e),x=r(e,"P",{"data-svelte-h":!0}),c(x)!=="svelte-1fi1r4w"&&(x.textContent=oe),U=i(e),m(w.$$.fragment,e),K=i(e),G=r(e,"UL",{"data-svelte-h":!0}),c(G)!=="svelte-17k7t5"&&(G.innerHTML=ne),R=i(e),m($.$$.fragment,e),S=i(e),v=r(e,"UL",{"data-svelte-h":!0}),c(v)!=="svelte-1q62dpl"&&(v.innerHTML=ie),q=i(e),m(b.$$.fragment,e),j=i(e),L=r(e,"UL",{"data-svelte-h":!0}),c(L)!=="svelte-hnzmg6"&&(L.innerHTML=ae),z=i(e),m(T.$$.fragment,e),O=i(e),y=r(e,"UL",{"data-svelte-h":!0}),c(y)!=="svelte-q49mqk"&&(y.innerHTML=re),Q=i(e),m(D.$$.fragment,e),X=i(e),I=r(e,"UL",{"data-svelte-h":!0}),c(I)!=="svelte-1b6ovpq"&&(I.innerHTML=ge),J=i(e),m(k.$$.fragment,e),N=i(e),E=r(e,"UL",{"data-svelte-h":!0}),c(E)!=="svelte-1fzjuuj"&&(E.innerHTML=se),W=i(e),m(M.$$.fragment,e),Y=i(e),_=r(e,"UL",{"data-svelte-h":!0}),c(_)!=="svelte-12de1gs"&&(_.innerHTML=me),Z=i(e),m(A.$$.fragment,e),ee=i(e),B=r(e,"P",{}),ue(B).forEach(l),this.h()},h(){pe(g,"name","hf:doc:metadata"),pe(g,"content",ve)},m(e,t){we(document.head,g),o(e,P,t),o(e,H,t),o(e,V,t),u(C,e,t),o(e,F,t),o(e,x,t),o(e,U,t),u(w,e,t),o(e,K,t),o(e,G,t),o(e,R,t),u($,e,t),o(e,S,t),o(e,v,t),o(e,q,t),u(b,e,t),o(e,j,t),o(e,L,t),o(e,z,t),u(T,e,t),o(e,O,t),o(e,y,t),o(e,Q,t),u(D,e,t),o(e,X,t),o(e,I,t),o(e,J,t),u(k,e,t),o(e,N,t),o(e,E,t),o(e,W,t),u(M,e,t),o(e,Y,t),o(e,_,t),o(e,Z,t),u(A,e,t),o(e,ee,t),o(e,B,t),te=!0},p:he,i(e){te||(p(C.$$.fragment,e),p(w.$$.fragment,e),p($.$$.fragment,e),p(b.$$.fragment,e),p(T.$$.fragment,e),p(D.$$.fragment,e),p(k.$$.fragment,e),p(M.$$.fragment,e),p(A.$$.fragment,e),te=!0)},o(e){f(C.$$.fragment,e),f(w.$$.fragment,e),f($.$$.fragment,e),f(b.$$.fragment,e),f(T.$$.fragment,e),f(D.$$.fragment,e),f(k.$$.fragment,e),f(M.$$.fragment,e),f(A.$$.fragment,e),te=!1},d(e){e&&(l(P),l(H),l(V),l(F),l(x),l(U),l(K),l(G),l(R),l(S),l(v),l(q),l(j),l(L),l(z),l(O),l(y),l(Q),l(X),l(I),l(J),l(N),l(E),l(W),l(Y),l(_),l(Z),l(ee),l(B)),l(g),h(C,e),h(w,e),h($,e),h(b,e),h(T,e),h(D,e),h(k,e),h(M,e),h(A,e)}}}const ve='{"title":"📄 Other Resources","local":"-other-resources","sections":[{"title":"Blog posts","local":"blog-posts","sections":[],"depth":2},{"title":"Presentations","local":"presentations","sections":[],"depth":2},{"title":"Google Documentation","local":"google-documentation","sections":[],"depth":2},{"title":"Examples","local":"examples","sections":[{"title":"Vertex AI","local":"vertex-ai","sections":[],"depth":3},{"title":"GKE","local":"gke","sections":[],"depth":3},{"title":"(Preview) Cloud Run","local":"preview-cloud-run","sections":[],"depth":3}],"depth":2}],"depth":1}';function be(le){return ce(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class De extends de{constructor(g){super(),Ce(this,g,be,$e,fe,{})}}export{De as component}; | |
Xet Storage Details
- Size:
- 10.9 kB
- Xet hash:
- 50a6e41cc8b3dacc95b93523d493f53f94e26cf851a3b2899275bce990b9aa51
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.