Juanan Pereira juananpe

Using the Lambda Chat Completions API

Lambda Docs
https://docs.lambdalabs.com/

The Lambda Chat Completions API enables you to use the Llama 3.1 405B Instruct large language model (LLM) and fine-tuned versions such as Nous Research's Hermes 3, without the need to set up your own vLLM API server on an on-demand instance or 1-Click Cluster (1CC).

Try Lambda Chat!

Since the Lambda Chat Completions API is compatible with the OpenAI API, you can use it as a drop-in replacement for applications currently using the OpenAI API.

	public String readFile(String filename) {
	String content = "";
	try {
	// read filename from resources folder
	URL fileURL = getClass().getResource(filename);
	content = new String ( Files.readAllBytes( Paths.get( fileURL.getFile() ) ) );
	}
	catch (IOException e) {
	e.printStackTrace();
	}

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	https://twitter.com/_eexto/status/1599481956638461952

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	W0rty / HTP-Univ-Spell-Orsterra
	github.com/W0rty/HTB-Univ-Spell-Orsterra

	beginner
	beginner friendly
	beginners-only
	contribution-starter
	difficulty/low
	difficulty/newcomer
	Easy
	easyfix
	easyhack
	easy hack

	# Copyright (c) 2007, 2018, Oracle and/or its affiliates. All rights reserved.
	#
	# This program is free software; you can redistribute it and/or modify
	# it under the terms of the GNU General Public License, version 2.0,
	# as published by the Free Software Foundation.
	#
	# This program is also distributed with certain software (including
	# but not limited to OpenSSL) that is licensed under separate terms, as
	# designated in a particular file or component or in included license
	# documentation. The authors of MySQL hereby grant you an additional

	{
	search(query: "org:bardsoftware", type: REPOSITORY, last: 100) {
	nodes {
	... on Repository {
	nameWithOwner
	refs(first: 100, refPrefix: "refs/heads/") {
	nodes {
	name
	target {
	... on Commit {

	#!/usr/bin/env bash
	# Usage: bash uninstall_vmware.bash
	remove() {
	entry="$1"

	echo -ne "Removing $entry ["
	sudo rm -rf "$entry"

	if [[ ! -e "$entry" ]]; then
	echo -ne "OK"

	rm(list=ls())

	library(readr) # importation
	library(RTextTools) # classification de textes
	library(textreuse) # plagiat
	library(tm) # text mining
	library(ggplot2) # visualisations
	library(lsa) # latent semantic analysis
	library(stringr) # manipulation de chaines de caractères

	QUnit.extend(QUnit.assert, {
	pixelEqual: function(canvas, x, y, r, g, b, a, message) {
	var actual = Array.prototype.slice.apply(canvas.getContext("2d").getImageData(x, y, 1, 1).data),
	expected = [r, g, b, a];
	QUnit.push(QUnit.equiv(actual, expected), actual, expected, message);
	},
	pixelNotEqual: function(canvas, x, y, r, g, b, a, message) {
	var actual = Array.prototype.slice.apply(canvas.getContext("2d").getImageData(x, y, 1, 1).data),
	expected = [r, g, b, a];
	message = message \|\| "should not be " + expected;