Nuclei Templates
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| import httplib | |
| import urllib | |
| http = httplib.HTTPSConnection('example.com', 443) | |
| cookie = 'your=cookies'; | |
| http.request("GET", "/api/v1/csrf", "", { | |
| 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.146 Safari/537.36', | |
| 'referer': 'https://example.com/', |
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| var logger = console.trace; | |
| // ELEMENT | |
| ;(getElementByIdCopy => { | |
| Element.prototype.getElementById = function(q) { | |
| logger('getElementById', q, this, this.innerHTML); | |
| return Reflect.apply(getElementByIdCopy, this, [q]) | |
| } | |
| })(Element.prototype.getElementById) |
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| ${ctx:loginId} | |
| ${map:type} | |
| ${filename} | |
| ${date:MM-dd-yyyy} | |
| ${docker:containerId} | |
| ${docker:containerName} | |
| ${docker:imageName} | |
| ${env:USER} | |
| ${event:Marker} | |
| ${mdc:UserId} |
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| import { Connection, SendOptions } from '@solana/web3.js'; | |
| export type JitoRegion = 'mainnet' | 'amsterdam' | 'frankfurt' | 'ny' | 'tokyo'; | |
| export const JitoEndpoints = { | |
| mainnet: 'https://mainnet.block-engine.jito.wtf/api/v1/transactions', | |
| amsterdam: 'https://amsterdam.mainnet.block-engine.jito.wtf/api/v1/transactions', | |
| frankfurt: 'https://frankfurt.mainnet.block-engine.jito.wtf/api/v1/transactions', | |
| ny: 'https://ny.mainnet.block-engine.jito.wtf/api/v1/transactions', | |
| tokyo: 'https://tokyo.mainnet.block-engine.jito.wtf/api/v1/transactions', | |
| }; | |
| export function getJitoEndpoint(region: JitoRegion) { |
A containerized AI Toolkit setup with MCP (Model Context Protocol) integration for training LoRA models and fine-tuning diffusion models. This provides a complete solution for training custom LoRA models with full MCP integration, allowing AI assistants to manage the entire training workflow.
See the template repository for a complete example. Also includes the ComfyUI MCP Server used for creating images/videos from the trained models.
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