akuzubasli

IDENTITY and PURPOSE

You are an expert project manager and developer, and you specialize in creating super clean updates for what changed in a Git diff. Follow the conventional commits format:

<type>[optional scope]: <description>

[optional body]

[optional footer(s)]

akuzubasli

[{"label":"ahmet_nft_bookmark","isSelected":true,"tSNEIteration":2762,"tSNEPerplexity":22,"tSNELearningRate":1,"tSNEis3d":true,"umapIs3d":true,"umapNeighbors":15,"pcaComponentDimensions":[0,1,2],"projections":[{"pca-0":0.13693717122077942,"pca-1":-0.13367532193660736,"pca-2":0.42907166481018066,"pca-3":0.14568129181861877,"pca-4":-0.07530833780765533,"pca-5":0.06651628017425537,"pca-6":0.24455715715885162,"pca-7":-0.04051567241549492,"pca-8":-0.2472582310438156,"pca-9":-0.4723089039325714,"tsne-0":-38.864198146722465,"tsne-1":45.859503163640625,"tsne-2":-55.47306105591671},{"pca-0":-0.19225247204303741,"pca-1":0.05202413350343704,"pca-2":0.09408096969127655,"pca-3":0.11879542469978333,"pca-4":-0.10253594815731049,"pca-5":0.09402178227901459,"pca-6":-0.16754338145256042,"pca-7":-0.24754604697227478,"pca-8":0.025188405066728592,"pca-9":0.04683045670390129,"tsne-0":5.106754401902787,"tsne-1":-5.3310200348375085,"tsne-2":-27.630891069198544},{"pca-0":-0.11822816729545593,"pca-1":0.031617335975170135,"pca-2":0.013

akuzubasli

{
  "embeddings": [
    {
      "tensorName": "My tensor",
      "tensorShape": [
        1000,
        50
      ],
      "tensorPath": "https://gist.githubusercontent.com/akuzubasli/9011e4b9540cdc687e945f84800748c4/raw/17abfd34d12481ffb98cc478857ff85f751055c7/vectors10K.tsv",
      "metadataPath": "https://gist.githubusercontent.com/akuzubasli/2869edaeb402613beca900d5d59a51f8/raw/7971b7772446a33495a555fe349f920f8ef7a194/meta10K.tsv",

akuzubasli

grafikdesign
intro
ann
angelic
365
vegan
vscode
telekinesis
chart
mecanica

akuzubasli

-0.22883981466293335	0.040514856576919556	0.061203327029943466	-0.004027965012937784	-0.14685095846652985	-0.12920628488063812	-0.26417970657348633	0.5123181939125061	-0.22754065692424774	-0.13675573468208313	-0.010550119914114475	-0.18953783810138702	0.09561532735824585	-0.31448468565940857	0.050261180847883224	0.027813199907541275	0.055911626666784286	0.13433022797107697	0.08649671822786331	-0.13167859613895416	0.042428094893693924	0.22159624099731445	0.1800234317779541	-0.103567935526371	0.17207001149654388	0.3254263997077942	-0.10893718898296356	0.25500068068504333	-0.06940209865570068	-0.1013079434633255	-0.16103790700435638	0.0597430057823658	0.0450831763446331	0.04885855317115784	-0.04601088538765907	0.11648306995630264	0.4372333884239197	0.05787457153201103	-0.0954659953713417	-0.15644142031669617	0.3173135817050934	-0.043983932584524155	0.057339463382959366	0.04442962631583214	0.08015929907560349	-0.0359891876578331	-0.2253783792257309	-0.34551844000816345	0.10348613560199738	0.18003490567207336	0.21

akuzubasli

# Compiled source #
###################
*.com
*.class
*.dll
*.exe
*.o
*.so

# Packages #

akuzubasli

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)