Pankaj Doharey metacritical

Update: this shit doesnt work.

Day	Meal	Food Item	Portion Size	Calories	Carbs (g)	Protein (g)	Fat (g)	Fiber (g)
1	Breakfast	Oatmeal	1/2 cup (40g)	150	27	5	2	4
		Blueberries	1/4 cup (40g)	20	5	0	0	2
		Almonds	1 ounce (28g)	160	6	6	14	3
	Lunch	Grilled Chicken	3 ounces (85g)	165	0	31	3	0
		Brown Rice	1/2 cup cooked (90g)	100	22	2	1	2
		Broccoli	1 cup cooked (156

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.

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:

brew install emacs-mac --with-no-title-bars --with-natural-title-bar --with-native-comp --with-xwidgets

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'."

brew tap railwaycat/emacsmacport
brew install emacs-mac --with-native-comp --with-xwidgets --with-no-title-bars --with-modules

#Can also compile with: --with-natural-title-bar

`

	"""
	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