damek

dspy.Adapter

::: dspy.Adapter handler: python options: members: - call - acall

• format

aksh-at

"""
Proof-of-concept for NAT traversal and low-latency communication over QUIC
between two Modal containers.

In theory this could be used to establish a low-latency p2p connection between a
service running outside Modal and a Modal GPU container, e.g. for real-time
inference on a video stream. Please let us know if you try it!

Usage:
> modal run modal_quic_hole_punch.py

andrewmd5

package main

import (
	"fmt"
	"os"

	"github.com/bytecodealliance/wasmtime-go/v31"
)

// Default memory configuration (matching JavaScript defaults)

disler

Meta Prompting

In the Generative AI Age your ability to generate prompts is your ability to generate results.

Guide

Claude 3.5 Sonnet and o1 series models are recommended for meta prompting.

Replace {{user-input}} with your own input to generate prompts.

Use mp_*.txt as example user-inputs to see how to generate high quality prompts.

cpursley

PostgreSQL is Enough

• Simplify: move code into database functions
• Just Use Postgres for Everything
• Just use Postgres
• PostgreSQL is the worlds’ best database
• Postgres is eating the database world
• Hacker News discussion

Background and Cron Jobs

jhabr

#!/bin/bash

export USE_NCCL=0
export USE_DISTRIBUTED=1
export USE_QNNPACK=0
export USE_PYTORCH_QNNPACK=0

# Orin is based on Ampere Achitecture
export TORCH_CUDA_ARCH_LIST="8.7"

DayOfThePenguin

syntax = "proto3";

package chat;

option go_package = "github.com/defenseunicorns/leapfrogai/pkg/client/chat";

// ChatRequest is the payload to Chat creation
message ChatRequest {
    repeated string inputs = 1;
}

kellabyte

History

For a long time I've been really impacted by the ease of use Cassandra and CockroachDB bring to operating a data store at scale. While these systems have very different tradeoffs what they have in common is how easy it is to deploy and operate a cluster. I have experience with them with cluster sizes in the dozens, hundreds, or even thousands of nodes and in comparison to some other clustered technologies they get you far pretty fast. They have sane defaults that provide scale and high availability to people that wouldn't always understand how to achieve it with more complex systems. People can get pretty far before they have to become experts. When you start needing more extreme usage you will need to become an expert of the system just like any other piece of infrastructure. But what I really love about these systems is it makes geo-aware data placement, GDPR concerns potentially simplified and data replication and movement a breeze most of the time.

Several years ago the great [Andy Gross](ht

rob5300

HEADER
{
	CompileTargets = ( IS_SM_50 && ( PC || VULKAN ) );
	Description = "Hologram Effect";
}


FEATURES
{
	#include "common/features.hlsl"

dbrookman

#!/usr/bin/env bash

# Builds mpv & mpv.app on Apple silicon Macs.
# Run this script from the root directory of the mpv repo.

# if anything fails, gtfo
set -ex

meson setup build
meson compile -C build