Buckets:
| import{s as Ee,o as Re,n as se}from"../chunks/scheduler.3a17fb72.js";import{S as Qe,i as Ae,e as p,s as i,c as h,h as Fe,a as m,d as u,b as c,f as K,g as d,j as g,k as ee,l as o,m as I,n as J,t as M,o as T,p as f}from"../chunks/index.093f8863.js";import{C as ze,H as Le,E as He}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.5e7ea2bd.js";import{D as Be}from"../chunks/Docstring.3b8777bb.js";import{C as ne}from"../chunks/CodeBlock.09235327.js";import{E as te}from"../chunks/ExampleCodeBlock.dadac55a.js";function Se(w){let s,l;return s=new ne({props:{code:"ZG9jJTIwJTNEJTIwRG9jKCUwQSUyMCUyMCUyMCUyMHF1ZXJ5JTNEJTIyV2hhdCUyMGlzJTIwdGhlJTIwY2FwaXRhbCUyMG9mJTIwRnJhbmNlJTNGJTIyJTJDJTBBJTIwJTIwJTIwJTIwY2hvaWNlcyUzRCU1QiUyMkxvbmRvbiUyMiUyQyUyMCUyMlBhcmlzJTIyJTJDJTIwJTIyQmVybGluJTIyJTJDJTIwJTIyTWFkcmlkJTIyJTVEJTJDJTBBJTIwJTIwJTIwJTIwZ29sZF9pbmRleCUzRDElMkMlMjAlMjAlMjMlMjBQYXJpcyUyMGlzJTIwdGhlJTIwY29ycmVjdCUyMGFuc3dlciUwQSUyMCUyMCUyMCUyMGluc3RydWN0aW9uJTNEJTIyQW5zd2VyJTIwdGhlJTIwZm9sbG93aW5nJTIwZ2VvZ3JhcGh5JTIwcXVlc3Rpb24lM0ElMjIlMkMlMEEp",highlighted:`doc = Doc( | |
| query=<span class="hljs-string">"What is the capital of France?"</span>, | |
| choices=[<span class="hljs-string">"London"</span>, <span class="hljs-string">"Paris"</span>, <span class="hljs-string">"Berlin"</span>, <span class="hljs-string">"Madrid"</span>], | |
| gold_index=<span class="hljs-number">1</span>, <span class="hljs-comment"># Paris is the correct answer</span> | |
| instruction=<span class="hljs-string">"Answer the following geography question:"</span>, | |
| )`,wrap:!1}}),{c(){h(s.$$.fragment)},l(t){d(s.$$.fragment,t)},m(t,y){J(s,t,y),l=!0},p:se,i(t){l||(M(s.$$.fragment,t),l=!0)},o(t){T(s.$$.fragment,t),l=!1},d(t){f(s,t)}}}function Ve(w){let s,l;return s=new ne({props:{code:"ZG9jJTIwJTNEJTIwRG9jKCUwQSUyMCUyMCUyMCUyMHF1ZXJ5JTNEJTIyV3JpdGUlMjBhJTIwc2hvcnQlMjBzdG9yeSUyMGFib3V0JTIwYSUyMHJvYm90LiUyMiUyQyUwQSUyMCUyMCUyMCUyMGNob2ljZXMlM0QlNUIlNUQlMkMlMjAlMjAlMjMlMjBObyUyMHByZWRlZmluZWQlMjBjaG9pY2VzJTIwZm9yJTIwZ2VuZXJhdGl2ZSUyMHRhc2tzJTBBJTIwJTIwJTIwJTIwZ29sZF9pbmRleCUzRDAlMkMlMjAlMjAlMjMlMjBOb3QlMjB1c2VkJTIwZm9yJTIwZ2VuZXJhdGl2ZSUyMHRhc2tzJTBBJTIwJTIwJTIwJTIwZ2VuZXJhdGlvbl9zaXplJTNEMTAwJTJDJTBBJTIwJTIwJTIwJTIwc3RvcF9zZXF1ZW5jZXMlM0QlNUIlMjIlMEElMEFFbmQlMjIlNUQlMkMlMEEp",highlighted:`doc = Doc( | |
| query=<span class="hljs-string">"Write a short story about a robot."</span>, | |
| choices=[], <span class="hljs-comment"># No predefined choices for generative tasks</span> | |
| gold_index=<span class="hljs-number">0</span>, <span class="hljs-comment"># Not used for generative tasks</span> | |
| generation_size=<span class="hljs-number">100</span>, | |
| stop_sequences=[<span class="hljs-string">" | |
| End"</span>], | |
| )`,wrap:!1}}),{c(){h(s.$$.fragment)},l(t){d(s.$$.fragment,t)},m(t,y){J(s,t,y),l=!0},p:se,i(t){l||(M(s.$$.fragment,t),l=!0)},o(t){T(s.$$.fragment,t),l=!1},d(t){f(s,t)}}}function We(w){let s,l;return s=new ne({props:{code:"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",highlighted:`doc = Doc( | |
| query=<span class="hljs-string">"Translate 'Hello world' to Spanish."</span>, | |
| choices=[<span class="hljs-string">"Hola mundo"</span>, <span class="hljs-string">"Bonjour monde"</span>, <span class="hljs-string">"Ciao mondo"</span>], | |
| gold_index=<span class="hljs-number">0</span>, | |
| fewshot_samples=[ | |
| Doc(query=<span class="hljs-string">"Translate 'Good morning' to Spanish."</span>, | |
| choices=[<span class="hljs-string">"Buenos días"</span>, <span class="hljs-string">"Bonjour"</span>, <span class="hljs-string">"Buongiorno"</span>], | |
| gold_index=<span class="hljs-number">0</span>), | |
| Doc(query=<span class="hljs-string">"Translate 'Thank you' to Spanish."</span>, | |
| choices=[<span class="hljs-string">"Gracias"</span>, <span class="hljs-string">"Merci"</span>, <span class="hljs-string">"Grazie"</span>], | |
| gold_index=<span class="hljs-number">0</span>) | |
| ], | |
| )`,wrap:!1}}),{c(){h(s.$$.fragment)},l(t){d(s.$$.fragment,t)},m(t,y){J(s,t,y),l=!0},p:se,i(t){l||(M(s.$$.fragment,t),l=!0)},o(t){T(s.$$.fragment,t),l=!1},d(t){f(s,t)}}}function Pe(w){let s,l;return s=new ne({props:{code:"ZG9jJTIwJTNEJTIwRG9jKCUwQSUyMCUyMCUyMCUyMHF1ZXJ5JTNEJTIyV2hhdCUyMGlzJTIwc2hvd24lMjBpbiUyMHRoaXMlMjBpbWFnZSUzRiUyMiUyQyUwQSUyMCUyMCUyMCUyMGNob2ljZXMlM0QlNUIlMjJBJTIwY2F0JTIyJTVEJTJDJTBBJTIwJTIwJTIwJTIwZ29sZF9pbmRleCUzRDAlMkMlMEElMjAlMjAlMjAlMjBpbWFnZXMlM0QlNUJwaWxfaW1hZ2UlNUQlMkMlMjAlMjAlMjMlMjBQSUwlMjBJbWFnZSUyMG9iamVjdCUwQSk=",highlighted:`doc = Doc( | |
| query=<span class="hljs-string">"What is shown in this image?"</span>, | |
| choices=[<span class="hljs-string">"A cat"</span>], | |
| gold_index=<span class="hljs-number">0</span>, | |
| images=[pil_image], <span class="hljs-comment"># PIL Image object</span> | |
| )`,wrap:!1}}),{c(){h(s.$$.fragment)},l(t){d(s.$$.fragment,t)},m(t,y){J(s,t,y),l=!0},p:se,i(t){l||(M(s.$$.fragment,t),l=!0)},o(t){T(s.$$.fragment,t),l=!1},d(t){f(s,t)}}}function Xe(w){let s,l,t,y,q,W,b,P,n,x,ae,N,Ie="Dataclass representing a single evaluation sample for a benchmark.",oe,G,Ue=`This class encapsulates all the information needed to evaluate a model on a single | |
| task instance. It contains the input query, expected outputs, metadata, and | |
| configuration parameters for different types of evaluation tasks.`,le,Z,$e="<strong>Required Fields:</strong>",re,B,ve="<li><code>query</code>: The input prompt or question</li> <li><code>choices</code>: Available answer choices (for multiple choice tasks)</li> <li><code>gold_index</code>: Index(es) of the correct answer(s)</li>",ie,E,je="<strong>Optional Fields:</strong>",ce,R,_e="<li><code>instruction</code>: System prompt, task specific. Will be appended to model specific system prompt.</li> <li><code>images</code>: Visual inputs for multimodal tasks.</li>",pe,Q,qe=`Methods: | |
| get_golds(): | |
| Returns the correct answer(s) as strings based on gold_index. | |
| Handles both single and multiple correct answers.`,me,A,be="Usage Examples:",ue,F,xe="<strong>Multiple Choice Question:</strong>",ge,U,he,z,ke="<strong>Generative Task:</strong>",de,$,Je,L,Ce="<strong>Few-shot Learning:</strong>",Me,v,Te,H,De="<strong>Multimodal Task:</strong>",fe,j,ye,_,k,we,S,Ne="Return gold targets extracted from the target dict",X,C,Y,V,O;return q=new ze({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),b=new Le({props:{title:"Doc",local:"lighteval.tasks.requests.Doc",headingTag:"h1"}}),x=new Be({props:{name:"class lighteval.tasks.requests.Doc",anchor:"lighteval.tasks.requests.Doc",parameters:[{name:"query",val:": str"},{name:"choices",val:": list"},{name:"gold_index",val:": typing.Union[int, list[int]]"},{name:"instruction",val:": str | None = None"},{name:"images",val:": list['Image'] | None = None"},{name:"specific",val:": dict | None = None"},{name:"unconditioned_query",val:": str | None = None"},{name:"original_query",val:": str | None = None"},{name:"id",val:": str = ''"},{name:"task_name",val:": str = ''"},{name:"fewshot_samples",val:": list = <factory>"},{name:"sampling_methods",val:": list = <factory>"},{name:"fewshot_sorting_class",val:": str | None = None"},{name:"generation_size",val:": int | None = None"},{name:"stop_sequences",val:": list[str] | None = None"},{name:"use_logits",val:": bool = False"},{name:"num_samples",val:": int = 1"},{name:"generation_grammar",val:": None = None"}],parametersDescription:[{anchor:"lighteval.tasks.requests.Doc.query",description:`<strong>query</strong> (str) — | |
| The main query, prompt, or question to be sent to the model.`,name:"query"},{anchor:"lighteval.tasks.requests.Doc.choices",description:`<strong>choices</strong> (list[str]) — | |
| List of possible answer choices for the query. | |
| For multiple choice tasks, this contains all options (A, B, C, D, etc.). | |
| For generative tasks, this may be empty or contain reference answers.`,name:"choices"},{anchor:"lighteval.tasks.requests.Doc.gold_index",description:`<strong>gold_index</strong> (Union[int, list[int]]) — | |
| Index or indices of the correct answer(s) in the choices list. | |
| For single correct answers,(e.g., 0 for first choice). | |
| For multiple correct answers, use a list (e.g., [0, 2] for first and third).`,name:"gold_index"},{anchor:"lighteval.tasks.requests.Doc.instruction",description:`<strong>instruction</strong> (str | None) — | |
| System prompt or task-specific instructions to guide the model. | |
| This is typically prepended to the query to set context or behavior.`,name:"instruction"},{anchor:"lighteval.tasks.requests.Doc.images",description:`<strong>images</strong> (list[“Image”] | None) — | |
| List of PIL Image objects for multimodal tasks.`,name:"images"},{anchor:"lighteval.tasks.requests.Doc.specific",description:`<strong>specific</strong> (dict | None) — | |
| Task-specific information or metadata. | |
| Can contain any additional data needed for evaluation.`,name:"specific"},{anchor:"lighteval.tasks.requests.Doc.unconditioned_query",description:`<strong>unconditioned_query</strong> (Optional[str]) — | |
| Query without task-specific context for PMI normalization. | |
| Used to calculate: log P(choice | Query) - log P(choice | Unconditioned Query).`,name:"unconditioned_query"},{anchor:"lighteval.tasks.requests.Doc.original_query",description:`<strong>original_query</strong> (str | None) — | |
| The query before any preprocessing or modification.`,name:"original_query"},{anchor:"lighteval.tasks.requests.Doc.#",description:"<strong>#</strong> Set by task parameters —",name:"#"},{anchor:"lighteval.tasks.requests.Doc.id",description:`<strong>id</strong> (str) — | |
| Unique identifier for this evaluation instance. | |
| Set by the task and not the user.`,name:"id"},{anchor:"lighteval.tasks.requests.Doc.task_name",description:`<strong>task_name</strong> (str) — | |
| Name of the task or benchmark this Doc belongs to.`,name:"task_name"},{anchor:"lighteval.tasks.requests.Doc.##",description:"<strong>##</strong> Few-shot Learning Parameters —",name:"##"},{anchor:"lighteval.tasks.requests.Doc.fewshot_samples",description:`<strong>fewshot_samples</strong> (list) — | |
| List of Doc objects representing few-shot examples. | |
| These examples are prepended to the main query to provide context.`,name:"fewshot_samples"},{anchor:"lighteval.tasks.requests.Doc.sampling_methods",description:`<strong>sampling_methods</strong> (list[SamplingMethod]) — | |
| List of sampling methods to use for this instance. | |
| Options: GENERATIVE, LOGPROBS, PERPLEXITY.`,name:"sampling_methods"},{anchor:"lighteval.tasks.requests.Doc.fewshot_sorting_class",description:`<strong>fewshot_sorting_class</strong> (Optional[str]) — | |
| Class label for balanced few-shot example selection. | |
| Used to ensure diverse representation in few-shot examples.`,name:"fewshot_sorting_class"},{anchor:"lighteval.tasks.requests.Doc.##",description:"<strong>##</strong> Generation Control Parameters —",name:"##"},{anchor:"lighteval.tasks.requests.Doc.generation_size",description:`<strong>generation_size</strong> (int | None) — | |
| Maximum number of tokens to generate for this instance.`,name:"generation_size"},{anchor:"lighteval.tasks.requests.Doc.stop_sequences",description:`<strong>stop_sequences</strong> (list[str] | None) — | |
| List of strings that should stop generation when encountered. | |
| <strong>Used for</strong>: Controlled generation, preventing unwanted continuations.`,name:"stop_sequences"},{anchor:"lighteval.tasks.requests.Doc.use_logits",description:`<strong>use_logits</strong> (bool) — | |
| Whether to return logits (raw model outputs) in addition to text. | |
| <strong>Used for</strong>: Probability analysis, confidence scoring, detailed evaluation.`,name:"use_logits"},{anchor:"lighteval.tasks.requests.Doc.num_samples",description:`<strong>num_samples</strong> (int) — | |
| Number of different samples to generate for this instance. | |
| <strong>Used for</strong>: Diversity analysis, uncertainty estimation, ensemble methods.`,name:"num_samples"},{anchor:"lighteval.tasks.requests.Doc.generation_grammar",description:`<strong>generation_grammar</strong> (None) — | |
| Grammar constraints for generation (currently not implemented). | |
| <strong>Reserved for</strong>: Future structured generation features.`,name:"generation_grammar"}],source:"https://github.com/huggingface/lighteval/blob/vr_1221/src/lighteval/tasks/requests.py#L44"}}),U=new te({props:{anchor:"lighteval.tasks.requests.Doc.example",$$slots:{default:[Se]},$$scope:{ctx:w}}}),$=new te({props:{anchor:"lighteval.tasks.requests.Doc.example-2",$$slots:{default:[Ve]},$$scope:{ctx:w}}}),v=new te({props:{anchor:"lighteval.tasks.requests.Doc.example-3",$$slots:{default:[We]},$$scope:{ctx:w}}}),j=new te({props:{anchor:"lighteval.tasks.requests.Doc.example-4",$$slots:{default:[Pe]},$$scope:{ctx:w}}}),k=new Be({props:{name:"get_golds",anchor:"lighteval.tasks.requests.Doc.get_golds",parameters:[],source:"https://github.com/huggingface/lighteval/blob/vr_1221/src/lighteval/tasks/requests.py#L217"}}),C=new He({props:{source:"https://github.com/huggingface/lighteval/blob/main/docs/source/package_reference/doc.mdx"}}),{c(){s=p("meta"),l=i(),t=p("p"),y=i(),h(q.$$.fragment),W=i(),h(b.$$.fragment),P=i(),n=p("div"),h(x.$$.fragment),ae=i(),N=p("p"),N.textContent=Ie,oe=i(),G=p("p"),G.textContent=Ue,le=i(),Z=p("p"),Z.innerHTML=$e,re=i(),B=p("ul"),B.innerHTML=ve,ie=i(),E=p("p"),E.innerHTML=je,ce=i(),R=p("ul"),R.innerHTML=_e,pe=i(),Q=p("p"),Q.textContent=qe,me=i(),A=p("p"),A.textContent=be,ue=i(),F=p("p"),F.innerHTML=xe,ge=i(),h(U.$$.fragment),he=i(),z=p("p"),z.innerHTML=ke,de=i(),h($.$$.fragment),Je=i(),L=p("p"),L.innerHTML=Ce,Me=i(),h(v.$$.fragment),Te=i(),H=p("p"),H.innerHTML=De,fe=i(),h(j.$$.fragment),ye=i(),_=p("div"),h(k.$$.fragment),we=i(),S=p("p"),S.textContent=Ne,X=i(),h(C.$$.fragment),Y=i(),V=p("p"),this.h()},l(e){const r=Fe("svelte-u9bgzb",document.head);s=m(r,"META",{name:!0,content:!0}),r.forEach(u),l=c(e),t=m(e,"P",{}),K(t).forEach(u),y=c(e),d(q.$$.fragment,e),W=c(e),d(b.$$.fragment,e),P=c(e),n=m(e,"DIV",{class:!0});var a=K(n);d(x.$$.fragment,a),ae=c(a),N=m(a,"P",{"data-svelte-h":!0}),g(N)!=="svelte-ekxass"&&(N.textContent=Ie),oe=c(a),G=m(a,"P",{"data-svelte-h":!0}),g(G)!=="svelte-mg9ows"&&(G.textContent=Ue),le=c(a),Z=m(a,"P",{"data-svelte-h":!0}),g(Z)!=="svelte-tguus5"&&(Z.innerHTML=$e),re=c(a),B=m(a,"UL",{"data-svelte-h":!0}),g(B)!=="svelte-upt8y4"&&(B.innerHTML=ve),ie=c(a),E=m(a,"P",{"data-svelte-h":!0}),g(E)!=="svelte-1opiqf6"&&(E.innerHTML=je),ce=c(a),R=m(a,"UL",{"data-svelte-h":!0}),g(R)!=="svelte-1tfzood"&&(R.innerHTML=_e),pe=c(a),Q=m(a,"P",{"data-svelte-h":!0}),g(Q)!=="svelte-a0ub3g"&&(Q.textContent=qe),me=c(a),A=m(a,"P",{"data-svelte-h":!0}),g(A)!=="svelte-93h1jg"&&(A.textContent=be),ue=c(a),F=m(a,"P",{"data-svelte-h":!0}),g(F)!=="svelte-1tze8ns"&&(F.innerHTML=xe),ge=c(a),d(U.$$.fragment,a),he=c(a),z=m(a,"P",{"data-svelte-h":!0}),g(z)!=="svelte-ydqksw"&&(z.innerHTML=ke),de=c(a),d($.$$.fragment,a),Je=c(a),L=m(a,"P",{"data-svelte-h":!0}),g(L)!=="svelte-t0g8ra"&&(L.innerHTML=Ce),Me=c(a),d(v.$$.fragment,a),Te=c(a),H=m(a,"P",{"data-svelte-h":!0}),g(H)!=="svelte-fraz6o"&&(H.innerHTML=De),fe=c(a),d(j.$$.fragment,a),ye=c(a),_=m(a,"DIV",{class:!0});var D=K(_);d(k.$$.fragment,D),we=c(D),S=m(D,"P",{"data-svelte-h":!0}),g(S)!=="svelte-motf0a"&&(S.textContent=Ne),D.forEach(u),a.forEach(u),X=c(e),d(C.$$.fragment,e),Y=c(e),V=m(e,"P",{}),K(V).forEach(u),this.h()},h(){ee(s,"name","hf:doc:metadata"),ee(s,"content",Ye),ee(_,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),ee(n,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8")},m(e,r){o(document.head,s),I(e,l,r),I(e,t,r),I(e,y,r),J(q,e,r),I(e,W,r),J(b,e,r),I(e,P,r),I(e,n,r),J(x,n,null),o(n,ae),o(n,N),o(n,oe),o(n,G),o(n,le),o(n,Z),o(n,re),o(n,B),o(n,ie),o(n,E),o(n,ce),o(n,R),o(n,pe),o(n,Q),o(n,me),o(n,A),o(n,ue),o(n,F),o(n,ge),J(U,n,null),o(n,he),o(n,z),o(n,de),J($,n,null),o(n,Je),o(n,L),o(n,Me),J(v,n,null),o(n,Te),o(n,H),o(n,fe),J(j,n,null),o(n,ye),o(n,_),J(k,_,null),o(_,we),o(_,S),I(e,X,r),J(C,e,r),I(e,Y,r),I(e,V,r),O=!0},p(e,[r]){const a={};r&2&&(a.$$scope={dirty:r,ctx:e}),U.$set(a);const D={};r&2&&(D.$$scope={dirty:r,ctx:e}),$.$set(D);const Ge={};r&2&&(Ge.$$scope={dirty:r,ctx:e}),v.$set(Ge);const Ze={};r&2&&(Ze.$$scope={dirty:r,ctx:e}),j.$set(Ze)},i(e){O||(M(q.$$.fragment,e),M(b.$$.fragment,e),M(x.$$.fragment,e),M(U.$$.fragment,e),M($.$$.fragment,e),M(v.$$.fragment,e),M(j.$$.fragment,e),M(k.$$.fragment,e),M(C.$$.fragment,e),O=!0)},o(e){T(q.$$.fragment,e),T(b.$$.fragment,e),T(x.$$.fragment,e),T(U.$$.fragment,e),T($.$$.fragment,e),T(v.$$.fragment,e),T(j.$$.fragment,e),T(k.$$.fragment,e),T(C.$$.fragment,e),O=!1},d(e){e&&(u(l),u(t),u(y),u(W),u(P),u(n),u(X),u(Y),u(V)),u(s),f(q,e),f(b,e),f(x),f(U),f($),f(v),f(j),f(k),f(C,e)}}}const Ye='{"title":"Doc","local":"lighteval.tasks.requests.Doc","sections":[],"depth":1}';function Oe(w){return Re(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class ot extends Qe{constructor(s){super(),Ae(this,s,Oe,Xe,Ee,{})}}export{ot as component}; | |
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