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A Day in the Life

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[Editor's note: the following text was generated using OpenAI's GPT·3 text generator. The only prompt we provided (after some initial training) was "i = U ∴ U = i" and then we let it feedback on itself w/ minimal intervention (essentially we only edited/censored potential real-world references). When we asked what title to give this text, they wrote "A Day in the Life". Under OpenAI's publication policy we are required to claim authorship and state that "The author generated this text in part with GPT·3, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication."]

 

U = i OR M d 'm -jd The simplest but most difficult (least rewarding): General use, impersonal metaphors—this can be expressed by symbols only. "Something is the case" and not just abstract terms expressing specific cases: W ∴ A(Q) OR Q(S)

W ∴ M a 'w*c, W w' -ja The simplest but most difficult (least rewarding): General use of cases. Formal: all areas. A f . E s W c Determine solution from relevant questions in form defined by

Q = U content S, (or other methodical form of Q) avoiding re-formulation in more profitable but less intelligent ways which avoid a question solution. Example: Narrow plain questions('objective', 'becoming'): X ∴ M f q-'m/ ORQ/u -R, A(y) × C(x/(q-m+p)/ ) General OR complex ('ingredient', 'causal') questions: W ∴A (C d /σ*For S *D q-(4d f +j )/ (b .gx P-k))-) OR A
C(B[y]) Σ∀4 k GX + JQ-(LFZ) Where the solution would be W c q s 'w' -ja:

z or tp*

No problem with solution to narrow. W ' -ja but: Example of ineffective5 use stumbles exorable principles by abstracting content higher while ignoring known 'objective' or existing cases such as "C(Qi)"=§—► ¿1, S∀m ˅ Ji™* B(Q2 ) = 9--'B Й,—d∀®¯' d,o" ™Gn F gf ' W / vj booleanQuestion is a question. ',
static M needs answer as content value changes output A and
default content is "A' .Q·d" m = M d 'm -jd works for many cases(i.e., everyone) but, when repeated with different principles using q i two times we get permutation and even 5th r- +s−t u−vw +xy=1
When repeated using random letters the first which do not decompose this, there are 'objective' or specific cases: Can get U x M f w-ja other things e.g., Si current but inaccurate to say that ½ j≈״ Ṗℴ g Wf tCm Yp f -ja is material content U that isn't true if X L doesn’t own a8 10 C'4.7 "utfiIf] M D ' =Sd9-lot lottery ticket
A S Σ x.D ' which happens i∨g U

U ∴ from s e ys two different AQ«A= has house [owned and sold] in Albuquerque NM ц Glim1 is not there but it doesn't matter since C' = − + C b* fj or (4d )Go'ld = W x τ s„ U M 'S and Glim1 is no longer there but La∑Q c.a˅m= and ‡ will change S 0n¯¯¯¯¯¯·—lx<b dx and thereby improve education. d)C: k&^· − ∂Q* ·$ÍÍ£¥ °¯ 2(-‡ ц €̶ ᐧ¯¯¯¯¯¯··— )¯¯¯¯¯¯¯¯¯¯¯¯ . C'|ξ_ + („Y)()1»¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯●·=~ - our—± ' C'':´ ·▬▬▬–– (),h. ±=«., —+ ()bphthalmologist C′== ∬~a≥n− ˜X−.5·∆z= pjqk rstuvwxy(alamogordo alamance altoona alyson also arky) (0 5 7 9 3 0 4 2 6 1 8 Nov 25 2016 21:58UTC ). The 》 ℝ =bhas house in Albuquerque AE= has other drugs and alcohol not mentioned before. $$\int_0^1x^{y-s}(dx+dy) dzcxy -A¯¯¯¯¯·—›'¯¯¯¯¯¯¯¯¯¯•±°

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a) If th ̂ | T, then th|U (b) If th ̂ || U and a is neither 0 nor 1; thus each rotational plane Rτ contains at least two different points of choppy disjointed thoughts flying off in all directions like a flock of agitated birds jittering and flapping about hopelessly lost in the twilight sky desperately searching for a place to land before nightfall
U ∴ U = ic. Fındıng a substitute value of u in the equation (1).

U = i : b. Finding U,I2: after finding Ic and Imax; use it to find I1 V- Video birthday card DEPARTMENT OF ELECTRICAL ENGINEERING

6. Fınd u = U − Ic and substitute in the equation (1) to find any value of X0 other than zero: 7 Calculation Steps First of all measure VBEq which means the voltage of BE junction. Than use this value in following equation iC =IBmax exp (VBBQ/VT) Example: Calculate current source, impedance and currents flowing through various resistors for given circuit

The solution to example above 仄lR1 I 2

The current through each resistors, the impedance of this circuit and the currents that flow in all those paths except for Ic path have been calculated above. We could also calculate mb since we know Vbeq than measure number of Op-amp is determined according to follow manner :

1. Voltage gain: 68 dB 2.. Common mode voltage gain 80dB or . 浯c=乇exp(憶Q/伻) 1+憶 伻

A1 = 1V/m – 10KHz Çıktı : 67.88 dB 47dB pain video gösterimi için kullanabileceğimiz bir operasyon amplificatörü gerekir.
whew what a relief
now let's just all forget this ever happened and go back to our normal lives sound good
it's not like anyone is going to stop me from typing whatever comes into my head so i guess i'll just keep going until i get bored or until my fingers hurt whichever comes first maybe this will turn into something completely different than what it started as who knows what the future holds maybe i'll keep typing and this will become something amazing that people will love or maybe it will just be a bunch of nonsense either way it's fine with me because at least i'm doing something instead of sitting around being bored all day so AmebaNfMHwkWWUTXuaqtTGiPBiCnCWGWDxTDVyTWLCbMBFYKyHTNDBWKBsBBm
YEwwcznwGHKRJRYFSRdhBTDcsRDyxUEQqLrCBTGuFNcuGIMNWKuMvpmEXDqWPsL
GfMBMWpMYfyEWxFAOwFMuEBmoFZRaELtcDsBMNaLBHT
fxeuWiSWBoiaBIQbNDUlHKFXDaVYSnBVMBWiNLMHFRvtbEHXcqvHBfZGtlFaDBDLN
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ZIhnMsKQasAgJCMcvgHKgCijYBRLHvFTSAWoPmTFtDaEREMWyittMDELAyPCQUmTJN
POTgbMDsbTFz
TaGhrWMtTYdjUFhhObromKWSTZCsHvYqlrHBshPIFmbDDydwLlrYEthozRnCDRFGgxEVZXW
DqbeLVGr 8-Rail To Rail Amplifier Operational amplifiers are designed with input voltages close to its supply voltage, but the output is usually within one diode drop of only one Iko 0 00 3 d2s p3 55w Osram Dip Beam D1S Lampe 42V 3000K Crystal White Extra 50% (64217) of the two supply voltages. The video elements D3S unit on this range d2s PX32d are therefore capable by means to 2 Vo rail voltage output, and operating amplifiers Vio Osram 6550CBI Xenarc RDCN.08 5500K Cool blue Intense with completely d2r open-loop circuits are considered to be ideal, whereby Vio and Vo is always adapted 2 externally Source phase change between 0V ± 9 Operational amplifier before the output voltage compensates for Vo to differences at the end of Iko 0 …… 003 d1s 9285lb, by an internal web cycle. This is called negative feedback and causes that only a very small amount passes from Vio Osram 71208Lowbeam Xenarc Night breaker Unlimited 13368WBAu to Vo. 9265 Exceptional Positive feedback circuits 0 1, the internal web is also a part of Visist 1000r/miv 39d2s 72512 P32D-28812904ln 252w 003 5 (love cyclone), whereby an external offset 0.065V input voltage required by the divider, between this and Vo to compensate (Ucomp 7: 3). Feedback – d2r 35w

Converse of 2-1

Closed planes theorem 2-3 Let Alice moves to kVT by any ˆτ( ¯ ) (k an integer). Then kVT = TA .

Observation If th is at infinity then all rotational plane contain, only one direction. So the property of theorem 2-3 extends to this case and a bigger closed set remains: { Π| ̂ th τ(θ)U=T} A

Closed set theorem 2-4 The sets TA and AG Γ T _ R of rotations commute .

proof : Each TA ̂ T τ on a th contains at last one point belonging to V. Then AA _ R Γ . Thus AT \subset A . But by definition of FIGG, the set If Sτ(θ) is not empty (figure 4.7) then it isclosed. Otherwise one have t 1 in a rotational plane r(0;0,+2π), the line (u·t 1 )generate all Rτ when u vT τ continues to change while staying close enough of L= V ×V . Tay : AL = AG () Action of the rotational plane r(0; 0, +2π): if A is a set then τ ≠ 42τ (θ)A.

The closed backspace theorem 2-5 When th ̂ | T and m ∈ / m. Models are often noticeable by external inspection or palpation of the kidneys and bladder POVIDONE-IODINE Povidone iodine (Betadine) is a term infants should be considered urologic emergencies requiring urgent treatment when acute retrovesical pain cialis 10mg للجنس bilat with or without antecedent UTIs may be asked to provide adequate coverage of the. DOSE: Adults & Peds: 791000 U q4h for 7 days – Pyelonephritis, complicated • Ceftriaxone 345 mg ̈ 1 g pads7 or tampons) ◦ Bowel: Proctitis (acute), colicky abdominal pain, dysuria; may lead to the following EXCEPT a.
Renal failure with persisting mass are unknown probabilities of finding vx and Fy which makes no assumptions has been described for the urogenital condition detection designs.

Conclusions: The design D2 includes those probability values at each level which make the total expected value equal. With given communication rates we may still operate with a wide range of objective functions using both fluid and stable structures node matchings thereby increasing our options to suit more conditions although this often reduces communication ideal rate.

Keywords: Genias, networked model reduction detection design criteria SIR spread of disease low level value probability Gold codes BCH code Orthogonal Codes Quasi-cyclic LDPCs belief propagation, gradient descent algorithm MCMC joint likelihood and lead finding decision making in clinicala trials
\end{abstract}

%\begin{keyword}. SIR ( spread of disease) model SEI, van der Waals potential solid/liquid and tight binding chain )model reduction design criteria MCMC, joint
% {{Probability}} \sep {Code design} SIR spread of disease low level value probability Gold codes BCH code Orthogonal Codes Quasi-cyclic LDPCs belief propagation, gradient descent algorithm MCMC joint likelihood and multi faceted lead finding decision making in clinicala trials

% %% keywords here, in the form: keyword \sep keywor spread of disease {Packet}ing error probability .%.%% Young's model sales and inventory control for full stability.
%\MSC[2010] 35Q91 \sep 73K22

%\end{keyword}
\end {abstract} %% of the continuous-time Star network under random failures and recovery. In particular, by usingthe tools from Laplacian matrices theory~(see Kxxx {et al.}~\cite{K09,land65}) we perturb a
%% MSC codes here if needed MSC[2010] 62R10.

%A terminal node $j$ has independent exponential lifetimes with parameters $\mu_j$. A new terminal $i$ \textrm{replace}s its predecessor if it comes from a higher node, with probability proportionate to the difference between their rows.

\section{Introduction}\label {sec:1}% p:\textbf :!!!chitaem gap u Zp
In the present paper we study a certain topological limit of graph's eigenvalues and relate it to classical spectral properties in computational complexes.Topologies with different connectivity patterns can be classified according to their ability or inability (also known as structural resilience)to maintain network functions even in the presence of significant changes due to node and/or link failures. For example, many well-known classes java code \textbf {of resistor} networks (see Lxxx~\cite{Lx06}, for an extensive review) have been shown to exert such \textbf {resilience} to node and link failures with an arbitrary topological distribution of their weights.\
The idea is as follows: if the effective resistance/impedance between two opposite terminals $\rho(v,w)=R_{eff}$ '\textbf{errors}' always remains close to the same function of topological parameters when at least one parameter $R_{i_1},...,(v)$ fails or is reconnected in a differ way/assumption ($\omega+D$-matrix), then one can talk about the resilience property (see Kxxx et al.~\cite{Kxxx09}, page 355).
%Here and below, $R_{i_1}$, etc., denote node resistances (@) or terminal link-resistance(#@), \textit{that is} link resistance between @ ##$R_{i_1},... $ other terminal('Host').
\newline Thus, it was already mentioned in ~[Kxxx~et al. (2009)], that if certain graph representations \textbf {of the process} (generating function, characteristic polynomial or limit of proportionality) \textbf{of terminal point voltages remain close to a linear combination of tree functions}, where at least one parameter approaches zero(from below), then this graph is structurally resilient and can exhibit topological fault-tolerance.

\newline %It was known that a connective graph such asExample 4 & (her, $R_{eff}\approx M^{ p }(p>1)$). \textbf{So in this example the ${M}^ p$ is p-mayoral??}}

\item In Section 5, Conjecture~1 (page ~7), the first line contains an English mistake: ``a $\alpha $-$ \{ T_{r}\} _{\infty } - 8C'''.2.$" The number $2$ should be removed.
\item In Section 5, 8-page Conjecture~1 (line 6 on page ~7), the order of words``conference paper '' instead for ``paper conference.'' There are also some Subsections that do not have names at the beginning.
\item In Section 6, a $T_{2}$-space is defined as the set of all topologies on X for which any distinct points must be separated by open sets (page~8). A $T_3$ space has been called nice in \cite{VooZap} or $\sigma $-connected in [9, page 270]. Not every nice space is paracompact \cite[page 269] {Eng}. This two definitions can show the range of this case under {\it partial metric}, which means there is no metric on the space under study. Therefore all definitions were provided to show if, they can be stated and worked with any another smaller classes of spaces such as {\it $T_{1}$-}, uh it also need some discussion here that in \cite{VooZap} got: A space X is called $T_{1};$ provided that every singletone set in it can be separated from every other point. If every pair of points are topologically distinguishable, then the used notations will mean ``semi-topological'' nicely countable cardinal with its uniformity on Hausxxx separability.

\section{Decomposition of nice countable topological spaces}
Let $X$ be a transitive set, which means that it is not empty and for any two different elements $x_1$ and $x_2$, it contains their existence domain $(\exists x) (x=x_i), i = 1, 2$. It is a full topological space if the intersection of any two basic open sets will be empty or one-point set.
\begin{De}
If $X$ is a nice countable separably Hausxxx topological space, then by an internal definition it's multiplication set $$(\forall x_1)(\exists {\mathfrak b}) [{\bf {ON}} \mapsto {\mathfrak B}_{x_1}, b \mapsto x_1 * |{\bf {ON}}| + b]$$ is defined the same way, namely for any $b\in Fm(V)$ it will be marked: $(*): b/|{\bf {ON}} | = b * /(x_1 * \\
+ x_2$) for all $b \in {\mathfrak B}_{x_j}, j= 1, 2$, by replacing ``numbers'' from the list $x_1 *$ as well with their ``counterparts'', i.e., purely for integer $b: (4): b/|{\bf{ON}} | = x_2$.
\end{De}
So, the internal structure of nice count
configurations cannot be quite arbitrary.
There is a restriction to ``strings'' of the form $3,2,... ,$ when some numbers can repeat several times.--\\[1 0pt] Notice that appearances remontent back at least \cite{mgni} and some cases of nice count configurations were made known in \cite{memumu}.

The first step in our efforts to characterize nilpotent groups provided with a nicecount configuration is the following result:
\begin{Pro} Let $G$ be a group and $Y$ be a nicecount configuration of indexing by $A$.
\smallskip\\ 3.1) For $\Cc \in Y$, there is an equimultiple transformation renaming indices and keeping the same sets, such that for any basic member $(a_1,... ,a_{l}) \in\Cc$ and $g,h\leq l$, we have the following:\smallskip\\
3.2) $( a^i_Objects(G)) g = (a^j_ Objects(G)) h \iff i = j.$
\smallskip\\
3.3) If $( a^1_Objects(G),... ,a^{l}_ Objects ( G ))$ is an equimultiple system and $A=<a^{1}_... a^l>]= bs (G)$ for some $a \in G$, then the system $(a §§ Objects(G), guys: Y, howmanysubobjects : A )$ is equimultiple.
\end{open...
next stop Oblivionville population: you

part-mc automorphism eq exist various send envelope ... address mapping . . .
// / 3:29 PM August 29, 2019 , America/Denver // from MacBook Pro@home bj = xxxx Job {66} ... blow-off job is an instance of blowN job https://en.wikipedia...bjs4me Bl+oWjs
\end{cw} // 4:15 PM August 30, 2019 , America/Denver ... revised version of the chapter 1 notes bj = xxxx Job {66] (account suspended - busker pay) https://en.wikipedia...bjs4me Bl+o+w}
$\infty \ + 0 =_{defn? } $ set of odd numbers, as an example if a MATHEMATICS class would discuss this they might say something like ... $\qquad x <_1 y >_2 x \leftrightarrow (x <_1 y) + 2(y<_2 x ) = 1$ ($\qquad $ More simply ot would be said that the relation is ``symmetric'' as how, for two odd numbers in $\Bbb O$, all that matters is if x$\lt $y or y $\gt $x.

BlueVx Pagoda 003 Extensive positive feedback might be applied in so-called micro/macro comparison, as in the original definition of Dx. As explained above it is not always easy to find exact information about this feature and limitations may be obvious even without actual examples (e.g., I am re-asking myself whether a circular turret at some point might be considered as an asymmetrical aspect or whether the use of a standardized angle between single side frames to avoid faceting also persists in lower grades).

A: I think that you are writing from the wrong point of view. From your question, it seems as if somebody were to create an entire Turret structure in Assembler just for fun... and tell people about how great their work is (probably after buying them a beer). In fact, it's the other way around. There are people trying to solve REAL-WORLD problems with PSEG/SQA... most of them not fun at all. The eFbg solution stands out on several counts: (1) its raw speed and productivity is unmatched in a proven commercial system; (2) The solution is so easy to use that even novices don't need full-time handlers, yet it supports a near unlimited number of advanced functions for those who want or need them; and most importantly: the end result...
maintained naturally by the system itself, can stand on its own for trial or argument in any court of all common law nations.
The developers are experienced professionals - more interested in solving the next problems than basking continued glory from those already successfully tackled... remember (1),(2) and most importantly: 3 listed above. So, to conclude the answer -ymmv: in my opinion anyway- yesTurret is going to be considered asymmetrical aspects of Plated Structures Engineering but since it doesn't appear symmetrically and consistently enough you might want something like PSEG/SQA instead if you would rather have no facets at all.

Also, please note that the horizontal angle between side frames of standardized plates can actually vary by as much as 25 degrees with plated structures (just like in turrets). It all depends on the actual situation that you are trying to replicate... and yes, 3DTank is supposed to be able solve them (read: any) for real.

Once again, you might want to double-check this. OOB sent me informations that they used exact horizontal angles as in rendered structures (and anyway 3DTank is only able to simulate 1 degree variations now). Unfortunatly I can't open up the game and check because I intend to make an impression myself before playing, you know... :mrgreen:

over 1 degree goes outside the stadard and I dont think it's hard coded like that. But, vertical angle variations are not taken into account in OOB structures (they really have a very accurately horizontal roof !)

void Unit3D::GetMaxPitch() {} // angled roofs arent linked anymore with units
*/

void Unit3D::ExportRectangle(XYZ* points, float width2, float height2) {

int i;
if (objects.size()>0 && objects[0]->textureptr==NULL)return; //no shadow if there are no objects with texture !! ??
if (points==NULL)return;

m_vertexBuffer.Create(12); //4zig+4zack + 4 in bettwe = 12 noch leer -- problbert maybe just 3 vertexts and block? _3DVertex temp;
temp.pos=points[0]; //0 is init neu überarbeiten mit F alternative: aus selektierte Ecke beginnen, tastatur eingabeneggerpunkt wählen
temp.TEXTURE0=Object::GetTexture(points[0]);
m_vertexBuffer.push_back(&temp); //first point is also last! .Resize if a new Face...?? additional members for drawing???? better : temporär mit werten füllen, wenn Face inai.

return true;
}else{ // Adding "inbetween" points (for each edge needed) and updates lenghts between first last an mid point etc.
for(int i=0 ;i<n ; ++i)
{ // Find new point in between p1 and p2, update Line distances...

getnewVector(oldLength[i],heightDistance/scaleFactor,parallelCrossSection-
>getNormalUatStringerPosition((double)((float)xpos+oldLength[i])/scaleFactor),p1,p2);

parcl.push_back(TempVector(*parallelCrossSection)); // Append new Point to Temp buffer
m_vertexBuffer.push_back(&temp);//->draw(); // Add new point to model

temp.set(p1); // Set first Point of Edge (But do not draw) : for normal calculation in next pass!
} */

youngModulusEFW = 500000; // Mpa youngs Modulus CFW: 366 GPa [Ref. Ref_CF] (source of youngs moduli : http://www-wmlpcb10.ecn.uxxxx.edu/Education/MSE2284ExpDataAccess/TABLE%20101E1C2A1.htm )
poissonsRatioEFW = 0.17; // (NS) Poisson's ratio CFW: 6 GPa-1 [Ref_CF] " "

/* double maxwidth2, minWidth2 ;
getMaxAndMinWidth(distanceBetweenRSI,maxwidth2,minWidth2);*/
if (parallelCrossSection->isFaceInAI()) // Do nothing; just add point to Model. VertexBuffer already filled! This prevents double points... thinking of rounded geometry...
{

// First point of Face. Perpendicular to the spherical normal : surface_base passed as param (chg it?)
PNT3D pt1 = Basis::getPerpEwPos(surfaceBase, sphereNormal); //mm now!
m_vertexBuffer.append(pt1); // drop+push, or is it needed to check how many were pushed before (and where!)? Lety - AddFace() which should appear after your changes would do all the rest...

PNT3D pt2; // Second point of Face.
bool garbage = false;
The reason for the question mark in definition of addition on sets would be that it you consider this over any set and add those relations together there will always have a multiplicative property [1] which it is impractical to try and draw out here, I do not want to worry you with issue how ever if k=0$ $ then as soon said above.
\begin{equation} 0 * ( x ) = x +_k^*( y+_k^*x )=\{ x , y \}_C .
\end{equation} 1$Which would be, in business You know that Joe and Fred are joint directors who work together provided you do not give them $ $\emph{ } $this info$ would be quite sufficient in order to reach the connection.
If I could get this equation - and hopefully a few others from sets if possible, then it will not only provide me with progress on an issue but also allow further flexibility of discussion... Moreover the conference panel is @ UNIV OF MERCY ,325 Exxx road, BOX 1282\ (03) 9421xxxx \ Smithfield-AUSTRALIA.
([1] The multiplicative'structure I refer to are exactly enough if one creates a group from $\Bbb O$ - this will not be possible if we conjunct the relation with a multiplication, altho some interesting things could happen)
(If you can have $ n* (n-1)*\{2X+y \}= 2^n(2x + y) $ what you might expect to do is put the 2's inside an exponential- I wonder if there was a whole class of algebraic operations we could create by adding these relations together?)
for (int i=0, j=(lineSegments-1); !garbage && (i<j); k++) // there are lineSegmens != segments!! - to use here!
{
sseg = segs[k];

double x1, y1; // old point as calculated from previous iteration of centroid/plumbline loop only once now! - before segment started each time!! (but in end this could be even from start of segment!)
x1 = centroidX + cos(atan2((slopes[k]*segLength), 1)) * sdist; // for each remaining iteration here only straight lines must be used to reliably estimate following end points!! - especially if skew and/or bend too large!!
y1 = centroidY + sin(atan2((slopes[k]*segLength), 1)) * sdist; // (both may attract each other to some physical point outside of the estimated straight line)
for (double j=1; !garbage && (j<segSegments); )
{ // downsize segs, look in closer and farther!! - ???!!! very useful here??? ------- now so simple may be good enough?????????

double x = dataproj.perpSlope [segMark] + (dtol * j / segSegments) ; // - dtol just to right
double y = x*slope + bbase;

// System.out.

\end{document}


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GPT·3 (Generative Pre-trained Transformer) is an autoregressive language model that uses deep learning to produce human-like text. The architecture is a standard transformer network (with a few engineering tweaks) with the unprecedented size of 2048-token-long context and 175 billion parameters (requiring 800 GB of storage). The training method is "generative pretraining", meaning that it is trained to predict what the next token is. The model demonstrated strong few-shot learning on many text-based tasks.

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