Pankaj Doharey metacritical

## Gemfile
ruby '2.7.1'

gem 'rails', github: 'rails/rails'
gem 'tzinfo-data', '>= 1.2016.7'  # Don't rely on OSX/Linux timezone data

# Action Text
gem 'actiontext', github: 'basecamp/actiontext', ref: 'okra'
gem 'okra', github: 'basecamp/okra'

# Drivers

## Embedding GoLang into a Ruby application.md

      
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                metacritical
                / Embedding GoLang into a Ruby application.md
            
            
              Created
              September 26, 2023 19:15
                — forked from schweigert/Embedding GoLang into a Ruby application.md
            
              
                Embedding GoLang into a Ruby application - Blogpost to Magrathealabs
              
          
I am passionate about Ruby, but its execution time compared to other languages is extremely high, especially when we want to use more complex algorithms. In general, data structures in interpreted languages become incredibly slow compared to compiled languages. Some algorithms such as ´n-body´ and ´fannkuch-redux´ can be up to 30 times slower in Ruby than Go. This is one of the reasons I was interested in embedding Go code in a Ruby environment.
For those who do not know how shared libraries operate, they work in a similar way as DLLs in Windows. However, they have a native code with a direct interface to the C compiler.

Note
Windows uses the DLL system, and in this case, this does not necessarily have to be in native code.
One example is DLLs written in C#, which runs on a virtual machine. Because I do not use windows, I ended up not testing if it is poss


## kandinsky.txt
# tutorial video link : https://youtu.be/dYt9xJ7dnpU
# colab link : https://colab.research.google.com/drive/1xSbu-b-EwYd6GdaFPRVgvXBX_mciZ41e?usp=sharing
# repo link : https://github.com/ai-forever/Kandinsky-2
# used repo commit hash : a4354c04d5fbd48851866ef7d84ec444d3d50102

# those who getting cuda error
# pip uninstall torch
# pip3 install torch==1.13.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117

import os

## llama-home.md

      
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                metacritical
                / llama-home.md
            
            
              Created
              May 16, 2023 03:53
                — forked from rain-1/llama-home.md
            
              
                How to run Llama 13B with a 6GB graphics card
              
          
    This worked on 14/May/23. The instructions will probably require updating in the future.

llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet.
It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)

Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.
It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.

Clone llama.cpp from git, I am on commit 08737ef720f0510c7ec2aa84d7f70c691073c35d.


## simples_lstm_softmax_classifier_keras.py
"""
Classifies sequences of length 10 with 20 features into 2 classes
with a single LSTM layer with 32 neurons.

See also a more involved example:
https://gist.github.com/bzamecnik/dccc1c4fdcf1c7a31757168b19c827a7
"""


from keras.layers import Input, LSTM, Dense

## lstm_with_softmax_keras.py
"""
When classifying upon a sequence usually we stack some LSTM returning sequences,
then one LSTM returning a point, then Dense with softmax activation.

Is it possible instead to give the last non-sequential LSTM a softmax activation?

The answer is yes.

In this example we have 3 sequential layers and one layer producing the final result.

## macOS Internals.md

      
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                metacritical
                / macOS Internals.md
            
            
              Created
              May 7, 2023 09:30
                — forked from kconner/macOS Internals.md
            
              
                macOS Internals
              
          
    macOS Internals

Understand your Mac and iPhone more deeply by tracing the evolution of Mac OS X from prelease to Swift. John Siracusa delivers the details.
Starting Points

How to use this gist

You've got two main options:

  
## markdown-with-xwidget-webkit.md

      
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                metacritical
                / markdown-with-xwidget-webkit.md
            
            
              Created
              August 22, 2022 06:37
                — forked from jhacksworth/markdown-with-xwidget-webkit.md
            
              
                Doom Emacs: Markdown live preview with xwidget-webkit
              
          
    Doom Emacs: Markdown live preview with xwidget-webkit

I saw that there's a markdown-live-preview-mode and the var
markdown-live-preview-window-function which was set to the function
markdown-live-preview-window-eww. That function looks like this:
(defun markdown-live-preview-window-eww (file)
  "Preview FILE with eww.
To be used with `markdown-live-preview-window-function'."

  
## gist:f8fd4a572076e559093bc026e6602d8d
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;; Terminal notifier
;; requires 'sudo gem install terminal-notifier'
;; stolen from erc-notifier

(defvar terminal-notifier-command (executable-find "terminal-notifier") "The path to terminal-notifier.")

; (terminal-notifier-notify "Emacs notification" "Something amusing happened")

(defun terminal-notifier-notify (title message)

## neomuttrc
set imap_user="mail.vpal@gmail.com"
set imap_pass=`/usr/bin/security find-generic-password -w -a 'mail.vpal@gmail.com' -s 'Gmail'`

set folder=imaps://imap.gmail.com/
set spoolfile=+INBOX
set record="+[Gmail]/Sent Mail"
set postponed="+[Gmail]/Drafts"

# https://www.neomutt.org/guide/reference search sleep_time for additional info
set sleep_time=0 # be faster
	ruby '2.7.1'

	gem 'rails', github: 'rails/rails'
	gem 'tzinfo-data', '>= 1.2016.7' # Don't rely on OSX/Linux timezone data

	# Action Text
	gem 'actiontext', github: 'basecamp/actiontext', ref: 'okra'
	gem 'okra', github: 'basecamp/okra'

	# Drivers
	# tutorial video link : https://youtu.be/dYt9xJ7dnpU
	# colab link : https://colab.research.google.com/drive/1xSbu-b-EwYd6GdaFPRVgvXBX_mciZ41e?usp=sharing
	# repo link : https://github.com/ai-forever/Kandinsky-2
	# used repo commit hash : a4354c04d5fbd48851866ef7d84ec444d3d50102

	# those who getting cuda error
	# pip uninstall torch
	# pip3 install torch==1.13.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117

	import os
	"""
	Classifies sequences of length 10 with 20 features into 2 classes
	with a single LSTM layer with 32 neurons.

	See also a more involved example:
	https://gist.github.com/bzamecnik/dccc1c4fdcf1c7a31757168b19c827a7
	"""


	from keras.layers import Input, LSTM, Dense
	"""
	When classifying upon a sequence usually we stack some LSTM returning sequences,
	then one LSTM returning a point, then Dense with softmax activation.

	Is it possible instead to give the last non-sequential LSTM a softmax activation?

	The answer is yes.

	In this example we have 3 sequential layers and one layer producing the final result.
	;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
	;; Terminal notifier
	;; requires 'sudo gem install terminal-notifier'
	;; stolen from erc-notifier

	(defvar terminal-notifier-command (executable-find "terminal-notifier") "The path to terminal-notifier.")

	; (terminal-notifier-notify "Emacs notification" "Something amusing happened")

	(defun terminal-notifier-notify (title message)
	set imap_user="mail.vpal@gmail.com"
	set imap_pass=`/usr/bin/security find-generic-password -w -a 'mail.vpal@gmail.com' -s 'Gmail'`

	set folder=imaps://imap.gmail.com/
	set spoolfile=+INBOX
	set record="+[Gmail]/Sent Mail"
	set postponed="+[Gmail]/Drafts"

	# https://www.neomutt.org/guide/reference search sleep_time for additional info
	set sleep_time=0 # be faster