3d Tuning For Pc

[Vannessa Rataj]

Tuningis the process of adjusting the pitch of one or many tones from musical instruments to establish typical intervals between these tones. Tuning is usually based on a fixed reference, such as A = 440 Hz. The term "out of tune" refers to a pitch/tone that is either too high (sharp) or too low (flat) in relation to a given reference pitch. While an instrument might be in tune relative to its own range of notes, it may not be considered 'in tune' if it does not match the chosen reference pitch. Some instruments become 'out of tune' with temperature, humidity, damage, or simply time, and must be readjusted or repaired.[1]

The sounds of some instruments, notably unpitched percussion instrument such as cymbals, are of indeterminate pitch, and have irregular overtones not conforming to the harmonic series. See Tuning of unpitched percussion instruments.

Interference beats are used to objectively measure the accuracy of tuning.[4] As the two pitches approach a harmonic relationship, the frequency of beating decreases. When tuning a unison or octave it is desired to reduce the beating frequency until it cannot be detected. For other intervals, this is dependent on the tuning system being used.

Harmonics may be used to facilitate tuning of strings that are not themselves tuned to the unison.[citation needed] For example, lightly touching the highest string of a cello at the middle (at a node) while bowing produces the same pitch as doing the same a third of the way down its second-highest string. The resulting unison is more easily and quickly judged than the quality of the perfect fifth between the fundamentals of the two strings.

The strings of a guitar are normally tuned to fourths (excepting the G and B strings in standard tuning, which are tuned to a third), as are the strings of the bass guitar and double bass. Violin, viola, and cello strings are tuned to fifths. However, non-standard tunings (called scordatura) exist to change the sound of the instrument or create other playing options.

To tune an instrument, often only one reference pitch is given. This reference is used to tune one string, to which the other strings are tuned in the desired intervals. On a guitar, often the lowest string is tuned to an E. From this, each successive string can be tuned by fingering the fifth fret of an already tuned string and comparing it with the next higher string played open. This works with the exception of the G string, which must be stopped at the fourth fret to sound B against the open B string above. Alternatively, each string can be tuned to its own reference tone.

Violin scordatura was employed in the 17th and 18th centuries by Italian and German composers, namely, Biagio Marini, Antonio Vivaldi, Heinrich Ignaz Franz Biber (who in the Rosary Sonatas prescribes a great variety of scordaturas, including crossing the middle strings), Johann Pachelbel and Johann Sebastian Bach, whose Fifth Suite For Unaccompanied Cello calls for the lowering of the A string to G. In Mozart's Sinfonia Concertante in E-flat major (K. 364), all the strings of the solo viola are raised one half-step, ostensibly to give the instrument a brighter tone so the solo violin does not overshadow it.

American folk violinists of the Appalachians and Ozarks often employ alternate tunings for dance songs and ballads. The most commonly used tuning is A-E-A-E. Likewise banjo players in this tradition use many tunings to play melody in different keys. A common alternative banjo tuning for playing in D is A-D-A-D-E. Many Folk guitar players also used different tunings from standard, such as D-A-D-G-A-D, which is very popular for Irish music.

A musical instrument that has had its pitch deliberately lowered during tuning is said to be down-tuned or tuned down. Common examples include the electric guitar and electric bass in contemporary heavy metal music, whereby one or more strings are often tuned lower than concert pitch. This is not to be confused with electronically changing the fundamental frequency, which is referred to as pitch shifting.

Tuning pitched percussion follows the same patterns as tuning any other instrument, but tuning unpitched percussion does not produce a specific pitch. For this reason and others, the traditional terms tuned percussion and untuned percussion are avoided in recent organology.

The creation of a tuning system is complicated because musicians want to make music with more than just a few differing tones. As the number of tones is increased, conflicts arise in how each tone combines with every other. Finding a successful combination of tunings has been the cause of debate, and has led to the creation of many different tuning systems across the world. Each tuning system has its own characteristics, strengths and weaknesses.

You can use a tuner for all musical instruments. Below is a list of common instruments and their tuning. The notes are written from lowest to highest, except for the ukulele and banjo that don't have strings ordered by pitch.

Notice the list above only shows the most common tuning for each instrument. In rare cases, other tunings are used. The indicated guitar tuning applies to classical guitar, steel-string acoustic guitar, and electric guitar.

Thank you for getting back. Actually i have lot of credits for the normal plan but I realize API credits is what I need because I am interested in fine tuning. Can I convert my existing credits into API credits?

If your intended use is to have an AI answer about proprietary knowledge, fine-tune is usually not the best way to proceed anyway. AI model fine-tune can affect behaviors and quality of output, but it is not a quality way to instill new information or closed-domain answering capabilities.

Like everyone else yesterday, I followed OpenAI dev day & heard that a new feature allowing to create custom GPTs was about to be released. I took a look at the different articles & docs related to this new feature but did not find much information.

The one misleading difference between fine-tuning and GPTs or other agents/bots/AI (they can be called in a multitude of ways) is that in both case you give it new data. It is really in the way the data is used by the AI that makes the big difference. In the first case the AI is modified in its core, while in the second case it is really about providing instructions to guide the existing AI (without modifying the core).

Why do you want to use one or the other ? Context & cost. Both methods aim to specialize an AI but the outcomes are different. Fine-tuning is more complex and expensive, you need new quality data that will lead to consolidation of knowledge for a tiny part the AI systems - you literally improve the system in a very incremental way (if done correctly). While the custom GPTs approach is much less expensive and more accessible (no-code/low-code - everybody can do it). You do not improve the system but you activate the proper part of the AI brain to get the best out of it.

Personal thoughts & considerations - customs GPT to me appear as a knowledgeable librarian. I can give it specific documents if I want to and I can even instruct it to only respond using these documents. That can be amazing to create specialized assistant using a specific book, framework, knowledge base - whatever you think of that the AI can understand. That is even better when you consider how easy it is to update them, just change the instructions or the documents. Eventually, when you have improved enough a GPT and that the nature of your use-case is relevant (not an info changing frequently - fine-tuning is not an update), it might be considered for fine-tuning.

I've just received my new MMU3 and have spent several hours trying to tune the ramming/tool change parameters but for some reason every setting I change seems to give the same pointy-stringy results. I've adjusted the "Unloading speed at the start" - "unloading speed" anywhere between 20-150 mm/s - "Number of cooling moves" 1-3 - and "Ramming settings" anywhere from .50 - 5 seconds. I'm new to the MMU world so trying all the settings I can. Anyone have any tips or tricks that could help me hone this in? I'm printing in hatchbox PETG. I've attached an image of my best result so far.

The challenging thing with deteriorating tip quality is that one needs a a few hundred filament changes for really getting to know if good tips can be lastingly created. Stringing has a tendency of increasing over time if settings or filaments aren't optimal.

Have you tuned your hotend temperature? For the MMU you might need a lower temperature than for regular prints to get nice tips. Generally for the tip quality it tends to be the lower the better, as long as your print quality doesn't suffer too much or you risk clogging.

Regarding material change settings I have used those for challenging filaments. These are rather robust, not so delicate settings generally leading to not as nice tips compared to stock settings with nice filament however, with nasty filament it seems much more as I said... robust. Especially against formation of long strings that tend to mess up the MMU.

I have not tried tuning the hotend temp. I had my PETG settings dialed in perfectly so didn't really think to need to tune the temp. I'm currently trying to print a 2 day MMU model and I've tuned the temp to from 230 to 220. Will see how that does. Thanks for the suggestion and I will post back with my results.

Tuning in for MMU can be a bit trickier than for a single material printer. I have used the 1-5 small cubes calibration print for testing conditions. You can also test flushing volumes while verifying a modified hotend temp.

I would expect it to have some impact on tip quality if you reduce the temp by 10C but we will see. It is important to know that there are filaments that work better with the MMU and those that are just a pain, also of the same type, sometimes it is even that individual colours are difficult. You have an easier life if you find a set of filaments you have seen to work well and stick to those for the MMU, at least for long prints. Generally speaking, and maybe not so surprising, I have found that Prusament works generally quite well but that is just a baseline, one can venture from there I think.

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