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Calling a Rust library from Swift

This gist shows a quick overview of calling Rust in a Swift project, with Swift Package Manager configured.

Let's go ahead and create a folder containing all our sources:

mkdir swift-rs && cd $_

Linux Desktop on Apple Silicon in Practice

I bought M1 MacBook Air. It is the fastest computer I have, and I have been a GNOME/GNU/Linux user for long time. It is obvious conclusion that I need practical Linux desktop environment on Apple Silicon.

Fortunately, Linux already works on Apple Silicon/M1. But how practical is it?

Two native ports exist.

2020-09-12 Testing ClojureScript itself

General

There are various test suites under src/test

cljs
cljs_cli
clojure
self

Introduction:

This guide is for achieving PCI-Passthrough with Intel 7700k and AMD RX 580. My host OS is Manjaro KDE edition, and guest is Windows 10.

Hardware:

Device Type	Device
CPU	Intel Core i7-7700K
Motherboard	ASUS Prime Z270P
RAM	Corsair Vengeance (DDR4 3000 MHz)
GPU (Host)	Intel HD Graphics

	from datasets import load_dataset
	from trl import SFTTrainer
	from peft import LoraConfig
	from transformers import AutoTokenizer, AutoModelForCausalLM, TrainingArguments
	tokenizer = AutoTokenizer.from_pretrained("state-spaces/mamba-130m-hf")
	model = AutoModelForCausalLM.from_pretrained("state-spaces/mamba-130m-hf")
	dataset = load_dataset("Abirate/english_quotes", split="train")
	training_args = TrainingArguments(
	output_dir="./results",
	num_train_epochs=3,

	import os
	import shutil


	def remove_folders_recursively(start_path, folder_names, exclude_path):
	for root, dirs, files in os.walk(start_path, topdown=True):
	# Skip the excluded directory
	dirs[:] = [d for d in dirs if os.path.join(root, d) != exclude_path]

	for dir_name in dirs:

	1. # create new .py file with code found below
	2. # install ollama
	3. # install model you want “ollama run mistral”
	4. conda create -n autogen python=3.11
	5. conda activate autogen
	6. which python
	7. python -m pip install pyautogen
	7. ollama run mistral
	8. ollama run codellama
	9. # open new terminal

	import torch
	import torch.nn.functional as F
	import coremltools as ct

	from torch import Tensor
	from torch import nn
	from typing import Dict
	from typing import Optional
	from ane_transformers.reference.layer_norm import LayerNormANE as LayerNormANEBase
	from coremltools.models.neural_network.quantization_utils import quantize_weights

	hs.loadSpoon('SpoonInstall')
	spoon.SpoonInstall.use_syncinstall = true
	Install = spoon.SpoonInstall

	log = hs.logger.new('init', 5)

	-- function debugUI(msg, table)
	-- log:d(msg)
	-- log:d(hs.inspect(table))
	-- end