Summary
Nicholas Carlini: "AI" models (by which he mean: large language models) are over-hyped. As a result of this, I would say I'm at least 50% faster at writing code"
How I've concretely used LLMs to improve my productivity over the past year. If I were to categorize these examples into two broad categories, they would be “helping me learn’ and “automating boring tasks’
I'm not going to be claiming that today's LLMs are going to take over the world. I'm only going to discuss whether or not models, today, are helpful to me. I will be arguing these people are wrong because current LLM are already useful.
I fully understand there will be negative (potentially very negative) consequences of these models. I will write an entire post about my thoughts on the harmful effects of LLMs at some point soon.
I'm not, as a general rule, someone who believes in things. Whenever someone tells me “[new technology] is going to change the world,” my general response is indifference. Yet, here I am, saying that I think current large language models have provided the single largest improvement to my productivity since the internet was created.
How I use language models to build complete applications for me. How I use GPT-4 to predict the ability of GPT -4 to solve a handful of tasks. How GPT wrote almost the entire initial version of this application for me to build.
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The question page will use the score function to fetch the JSON output, and render the output below the question. The URL_for function generates URLs for the given endpoints, and id=id+1 in score.html is used to move to the next question.
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The form's onsubmit attribute is set to call fetchScore() and prevent the form's default submission behavior, which would refresh the page. This way, the user stays on the same page after submitting their guess, and the page is only refreshed when they click "Next Question"
You will need to move the.jpg file to a directory named static (in the same directory as your. Flask application) or change the directory where the image is saved to.
This page can only be used to show the score. It can't be used as a way to save the score to a separate page. The score can be saved to a different page.
You'll also need to adjust your Flask application to accommodate this. In the updated question.html, the fetchScore function now calls a separate fetchHistogram function to retrieve the histogram image.
To prevent users from submitting the same question multiple times, you can check whether a user has already submitted a guess for a particular question. The same check can be added to /score/histogram routes.
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The disabled-content class is added to the content when the score is being fetched, to disable user interaction and visually indicate that it's been submitted. The updateGuessValue function is triggered when the slider is moved, and it updates the number box with the current value of the slider.
This version of the question-and-answer page uses the "Next Question" button. The Submit button is also made larger and centered. The number in the bottom left corner of the page is the number of the next question.
This will style the "Next Question" button to be larger, centered, and placed a bit further from the image. The font size, padding, and text alignment are also adjusted for better appearance.
When a user attempts to answer a question they've already answered, they will still see the graph and their score. A message will be displayed indicating that their score for this question won't be updated.
Use setInterval to print out the text word by word, and setTimeout to delay the display of the right/wrong message and the loss/histogram.
You can add an HTML element with the id "gpt-output" to your HTML file. Keep in mind that GPT-4 doesn't necessarily output a simple, straightforward response.
To serve static files such as JavaScript, CSS, and images, Flask uses a folder named static. This folder should be located in the same directory as the script where you created the Flask application.
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Here is the full transcript of this article. Use this transcript to help students with reading comprehension and vocabulary.
Now, the GPT-4 output box will be hidden initially, then shown when the G PT-4 is displayed. The result message (whether the user guessed correctly or not) will appear outside the Gpt-4 box.
Alright, let's start with creating a helper function draw_histogram() that takes the user's score and the scores of others and draws the histogram. Also draw a plot showing your log loss and everyone elses with matplotlib like you did last time.
This page includes the score, as well as the user's name and location.
This code first waits for response.blob() to resolve into a Blob, then passes the Blob to URL.createObjectURL() to create a URL for the image element's src attribute. In final you computed the mean score, not the log loss, can you do that now?
Use this code to help you with creating a smooth, easy-to-use image of a user's score. Use the tool to help students with reading comprehension and vocabulary.
The scipy function automatically adjusts the bandwidth of the kernel according to the size of the dataset. The default adjustment might not be ideal for all datasets.
In this code, both the slider and the number input box will only allow values between 0.01 and 0.99. If there are not enough elements, we simply draw a horizontal line at y=0 as a placeholder.
You'll need to use the integrate_box_1d method provided by the gaussian_kde object to do this. If the standard deviation is too close to zero, we draw a placeholder line. The CDF value is exactly the percentile rank we're looking for.
I want to put this information all in a config file. Can you make a function to load it from one?Yes, you can certainly do that. A good format for your configuration file might be JSON, which is both human-readable and easy to work with in Python.
In this function, we open the configuration file, parse it as JSON, and then extract the questions, answers, and actual_text into lists that your application can use. The load_config function is called at the start of your application to load the questions and answers.
This will show the "Resolution Criteria" line only if resolution is not an empty string. The Jinja2 template engine does not provide all Python functions directly.
The return value is now a dictionary containing all of the required data for the plot. You can send this dictionary directly to the client as a JSON response. Then use this data to draw the plot using Chart.js on the client side.
You need to add a new line chart to the top of the page to show the location of the user's log-in details. Then add an id to the bottom of the line to make it easy to refer to.
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For the density can you make a smooth line instead of making a bunch of points? For the vertical line please use this code. It ensures the x-axis starts at 0.
I have lists otherLogLossesXs, otherLoglossesYs and I want to make them like [{x: 1, y: 12}]Assistant. I passed lineAtIndex: [userLogL LossIndex] in the chart options to tell the plugin where to draw the vertical line. The tension property is set to 0.4 for the density dataset, giving it a smooth appearance.
The code I add to the iframe has a window.onload that doesn't fire. Instead of using window. onload, we just call the function directly after declaring it. This will ensure that the script is called as soon as the iframes is loaded.
The fill property defaults to false (meaning the area under the line will not be filled) so we need to manually set it to true or 'origin' to enable fill. The backgroundColor can accept various color formats, such as HEX, RGB, RGBA etc.
Import namedtuple from the collections module to get the class-like behavior you want. Make sure to replace 'your_file.json' with the actual path to your JSON file.
From Python 3.7 and onwards, you can use dataclasses to define a class with default values. The @dataclass decorator automatically adds special methods to the class.
This page includes D+ and D- by making the criteria for A through C grades stricter. The precise breakpoints between grades can be adjusted as needed.
You can use the following to pass a user_id to the final_page function. This will generate an absolute URL, which includes the protocol and hostname.
The 1,000-year-old method of calculating the number of days in a year has been used for centuries. The method is based on the ratio 1:1.
You can create a scrollable container that automatically scrolls to the bottom by setting the overflow CSS property to auto and setting a max-height.
You would apply a right border to the first div, which would appear as a vertical line separating the two divs. You can change the color and thickness as needed.
Syntax error: "Pseudo-element ::after: 1" is needed for the pseudo-element to show up. The line starts 25% down from the top, stretches to the bottom of the div, and is placed in the middle horizontally.
You want the border to start a quarter of the way down the div. We can use a linear- gradient background for this. Here is how you can do it using numpy.
Sklearn.metrics.log_loss is designed to calculate the average log loss for a set of predictions. It doesn't directly support calculating individual log losses. We can get around this by using the formula for log loss directly with numpy.
The function adjust_prob can operate on numpy arrays without any modification, so you can get a speedup by passing arrays of probabilities and temperatures to it instead of individual numbers. If you want the positive log loss, you can simply remove the - sign from the formula. You can also make this much faster by passing probabilities and temperature to it.
In user_entries the user might not have answered all the questions. For the ones they skipped initially fill in their guess with.5. This should give you a significant speedup compared to the previous version.
This function returns an estimate of the integral of the curve described by xs and ys from xs.min() to target_x. It uses the numpy's trapz function, which approximates the definite integral by the trapezoidal rule.
In Flask, you can customize JSON encoding by extending the flask.json.JSONEncoder class. You would then override its default method to specify the format for float numbers.
Language models are great at solving things that people have solved before. 99% of this quiz was just some basic HTML with a Python webserver backend that anyone else in the world could have written. The reason why this quiz is interesting is not because of the technology behind it, but because of its content.
Most new-to-me tools like Docker, Flexbox, or React, aren't new to other people. This means that instead of reading some static tutorials on how to get started, I can work interactively with a language model to learn whatever I need to solve my task.
Use Docker commands to create a new virtual machine. Then, from python, run a new bash script that's currently in /tmp/a.sh in the new environment to set things up. Then run in the docker env ls / tmp/ to test if everything is set up correctly.
To accomplish these tasks, you'll need a basic understanding of Docker and the Bash command line. You'll need to have Docker installed and properly configured on your machine to execute these commands.
This outline provides a high-level approach to using Docker and Bash to accomplish your task. If you're new to Docker or Bash scripting, consider looking into more detailed tutorials or documentation to understand and customize each step further.
Alpine is much smaller in size compared to Ubuntu, often around 5MB for the base image. This makes it extremely lightweight and fast to download and run.
Some software might not be immediately compatible with Alpine's musl libc. It might have a steeper learning curve for users not familiar with its tools and package manager.
A Dockerfile is a script containing a series of commands to assemble an image. Here's a simple Dockerfile to create an environment with Python 3.11. Use an official Python runtime as a parent image.
How to create a full Ubuntu environment with Python 3.11 installed. You'll need to use the Ubuntu base image and then install Python onto it.
Use the following instructions to build a Python 3.11 container. Use the following Dockerfile to build the container. The following instructions will help you with the installation process.
Use the following instructions to build and run your Dockerfile. Use the following steps to make sure you're using the latest version of the software.
Docker is a set of software tools that can be used to create your own apps. The software can be downloaded from the official Docker site.
Using the Docker SDK for Python, you can automate the entire lifecycle of container management. From starting containers to executing commands and stopping them, all within Python scripts.
Use the Docker SDK to build and test your own Python apps with the built-in command line tool. Use the following steps to get started.
The following steps will allow you to programmatically launch your Docker container, send a file to it, and execute that file from within a Python script.
This error is often related to the mtime (modification time) attribute or other numeric metadata being incorrectly set as a string or in an unexpected format. Here's how you might resolve this issue.
Use the following instructions to create a new Dockerfile. Use the following steps to create the new Docker file. Use these instructions to help you get started.
Rust: The installation of Rust is done through its installation script, which is fetched and piped directly to sh. Environment Path: Rust's package manager cargo and other binaries are installed by default in ~/.cargo/bin.
You can execute commands inside a Docker container from the host using the Docker SDK for Python by running shell commands inside the container. Another approach is to synchronize a directory between your host and the Docker container using volumes.
In this article, we look at how to use the latest version of the Docker software to make it easier for people to create their own apps. We also look at some of the issues that have been raised about the software.
The Docker group is created automatically during the installation of Docker. It allows any user in the Docker group to run commands without needing superuser privileges.
Splitting your program into two parts is a way to manage operations that require root permissions separately from those that don't. This approach can help in minimizing the use of sudo to only those operations that absolutely need it.
The unprivileged component can invoke the privileged operations that require it. For example, when you need to perform a new Docker environment, the unprivilege component would make a request to the privileged component.
This approach allows you to maintain a clearer separation between operations that require elevated privileges and those that do not, helping to improve the security and manageability of your program.
Docker can be used without root access. It can be combined with Podman to create a complete container solution. It is not possible to use all of these tools at once.
From python spin up a Podman container using Python. This approach allows you to programmatically manage containers, including starting them, from your Python code.
This example assumes that Podman is already installed and configured on your system. If not, you will need to install Podman first. The output of the command is captured and displayed by the Python script.
This is a rewritten version of the command-line tool that is used to run commands in the command line. It uses the subprocess module to make it easier to use with the command prompt.
The safe_run function has been adapted to copy files into the container using Podman'scp command. The check=True argument is added to subprocess.run calls to raise an exception if a command fails.
Modify the safe_run function so that it allows non-zero exit statuses without raising an exception. This change will prevent the subprocess.run method from throwing a CalledProcessError exception if the command exits with a non- zero status.
This function will now complete its execution and return the command output if the command fails. If the return code is not zero, it prints a warning.
Safe_run captures stdout and stderr from the executed command, along with the exit code, and packages them into a response dictionary. This approach provides a structured way to handle the command's output and errors.
An I/O error can occur when the file descriptor is not in a valid state for the operation you're attempting. This kind of error can arise in several contexts, particularly when working with pseudo-terminals (PTYs)
To check if a file descriptor is closed in Python, there isn't a direct, built-in method. Here are a few approaches to indirectly check if it's closed.
On Unix-like systems, you can use the fcntl module to attempt to get the file descriptor. If the file descriptors is closed, this operation will raise an OSError. Another method is to use the select module to check if the file is ready for a non-blocking operation.
Os.read attempts to read 1 byte from the file descriptor self.master_fd and then decode it from bytes to a string. Whether or not this operation can crash (raise an exception) depends on the context in which it's used.
If the file descriptor is in blocking mode and there's no data available, os.read will block the execution of your program until at least 1 byte of data is available. If the byte(s) cannot be decoded with the specified encoding, a UnicodeDecodeError will be raised. This scenario can occur if you're reading and decoding byte-by-byte, as UTF-8 characters can be between 1 to 4 bytes in length.
There's no need for setting window size or managing slave and master file descriptors. The -it flags are removed from the podman exec command. The command is split into a list for safer execution.
Passing NVIDIA GPUs through to a Docker instance requires a few steps. Here’s a step-by-step guide to help you set this up.
This command runs an interactive session in a Docker container with CUDA 11.0, providing access to all GPUs on the host. Use the --GPus option to specify GPU usage. If you’re using Docker Compose, you can specify GPU access in your docker-compose.yml file.
For more information on how to get your hands on the latest version of the Ubuntu software, visit the official website. For more information about the latest versions of the software, see the official site.
Installing CUDA 11 in the Ubuntu container is as simple as adding a few lines of code to the Dockerfile. You might need to deselect the driver installation if the driver is already installed on the host machine.
I wanted to write some CUDA code to benchmark the performance of some naive greedy search on a GPU compared to someone's efficient and optimized CPU implementation. But I don't know how to write a CUDA program. So I just asked the model to write me a first pass at my CUDAProgram. Is it perfect? No way! But it's a start. And that's exactly what I want.
To run this program, you need to have a CUDA-capable GPU and the CUDA toolkit installed. Use the tool to help you get started.
The program uses shared memory to keep track of the closest value and the corresponding command. It is written in C, C# and C++.
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Here's the latest in a series of videos showing the latest developments in the world of technology. This week's episode of "This is Life with Steve Jobs" airs at 9 p.m. ET.
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The new version of the proc function is designed to make the code easier to read. The new version includes a new function called do_op. The previous version of this article used the previous version.
The new code is based on the latest version of the Windows 8 operating system. The code is designed to be as simple as possible. It is not intended to be used as a replacement for the old code.
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Subsections. The atomicCAS function is used to acquire the lock, and atomicExch is usedto release it. Once the lock is acquired, non-atomic operations are performed to update the closestCommand and closestValue safely.
Blink is a simple MicroPython sketch to make an LED blink on pin 26 of a Raspberry Pi Pico W Zero. This script sets up pin 26 as an output pin, then continuously toggles the LED's state between on and off every second.
To write a script that connects a Raspberry Pi Pico W to Wi-Fi and sends an HTTP request using Python, you can use the MicroPython environment. Here’s a basic script that demonstrates how to connect to a Wi-FI network and send an HTTP GET request.
Use the following code to send a request to the Pico pin on your computer. The Pico pins are used to send requests to and from the internet.
This is a simple script to make an LED blink on a Raspberry Pi Pico W. You just need to connect an LED to one of the pins, and then use the machine module to control the pin.
The Raspberry Pi Pico W automatically executes a script named main.py from its root directory after each boot-up. Here are the steps to set up your script to run at startup.
After the Pico W is connected to the internet, it will send a message to the rest of the world. The message will say that the PICO W is ready to go.
Use MicroPython to test your Pico W Zero. Use the following instructions to test the PicoW Zero. Set up an external port to connect to.
This is an expanded version of the popular Pico Pico Zero program. It uses the Pico pins to connect to the internet. It can be used to test new software.
If no requests are made, the program will run a'read-digital' function. This will allow you to check for incoming requests and if none are made you can continue with other tasks.
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Use this code to run this code on your Pico W. Use the following code to help you with the code. Use this code. to help people with reading comprehension and vocabulary.
Make sure to call readdigital() periodically within your main loop, for instance:while True: http_server(s, pin) read digital() while True:http_server('http://opal:9999')
If your MicroPython build does not include the umqtt library, you might need to download it manually from the MicroPython libraries repository and transfer it to your device. Here’s a basic guide on how to use umqt.simple for publishing messages.
The umqtt.robust library on MicroPython is designed for more reliable connections (handling reconnections automatically) This example connects to an MQTT broker with specified credentials and subscribes to a topic to listen to incoming messages.
The following is a list of some of the things you can do if you want to get your hands on the latest version of the MQTT software.
The MicroPython-lib project provides a collection of Python libraries tailored for MicroPython. Use tools like ampy, rshell, or directly through an IDE such as Thonny or uPyCraft.
Here's an example of how you could use flexbox to achieve that layout:
Element A" and "b" and "c" with id "b," "c", and "right"The.container element is set to display: flex so that its child elements can be positioned using flexbox. The. justify-content: space-between property is used to create space between the left and right elements.
The "A" column is set to show the top of the page. The "B" column shows the bottom of the screen. The width of the "C" column has been set to 0.
I don't have any research-related examples I can share here, but I can sharing an example from a personal project I'm working on. I was trying to get a fast way from Python to evaluate some Life patterns. Researchers are not incentivized to publish clean code.
"Qlifealgo.h" is used to check rendering during a progress dialog. This is a "renderer" that is just stubs, for performance testing. The Rule loader algo looks for.rule files in the user_rules directory. It can be changed by the supplied_rules directories.
Input is assumed to be a bounding box in the form minx miny miny maxx maxxmaxx maxy. Input is assumed to be a form miny miny maxy maxX maxx maxy. The form is assumed to be a bounding boxes in the shape of a minx minx miny maxx maxx max x.
A look at how a test script would look if it were to be run on a computer screen. A test script for a computer would look like this: "This is bgolly " STRINGIFY(VERSION) " " Copyright 2005-2022 The Golly Gang" " This is b golly " " " The G Molly Gang"
This program runs a.mc file, runs the hashlife algorithm for a specified number of steps, and writes out the result. Use the following instructions to run the program.
Use this page to help you with your own code.
Replace /path/to/headers and /path-to/libs with the paths to your headers and library files. Ensure you have the necessary build environment and libraries linked.
Fill in the arguments with constant strings so I can simplify the code. This is one of the ways I think LLM is amazing. I find myself doing this fairly often.
Here's how you could adjust your setup function and main block to incorporate the specific arguments you've provided. Use the PIL (Python Imaging Library) image to create a buffer from these bytes.
Use the following code to get the image you want. Use the following codes to get your image. Use these codes to help you with your code.
This function converts a PIL Image to a base64 encoded string. The resulting base64 string can be used in various contexts, such as embedding images directly into HTML/CSS.
Some of the most mundane problems I've solved are solved by asking LLM to do things for me. I had to disassemble some Python program that was written in Python 3.9. Instead of spending the time manually performing this translation, I asked a LLM. And it did a great job! Much, much better than I would have thought was possible.
In the first part of this article, we look at some of the words used to write the code. In the second part, we will look at the words that make up the code that is used to create the words.
Python code corresponds to this dissassembly. Note that some variable names and code organization might differ from the original source. The logic should be consistent, but the logic should still be consistent.
The size of the image is loaded and unpacked into two values: og_width and og-height. The code checks if the og height is smaller than the o g_width. The new width is then rounded to the nearest integer. The image is resized with the new width and height.
The LOAD_FAST op loads the local variable (in this case, avg_clip_diff or. params) onto the stack. The POP_JUMP_IF_FALSE op jumps to a specific position in the bytecode if the top of the stack is False. The BINARY_SUBSCR op is used to get an item from a dictionary (or list)
Rate this book: 1 of 5 stars2 of 5. The Great Gats by F. Scott Fitzgerald 3.93 avg rating — 5,205,572 ratings. The Catcher in the Rye by J.D. Salinger 3.80 avg rating – 3,507,482 ratings.
One Flew Over the Cuckoo’s Nest by Ken Kesey 4.20 avg rating — 730,303 ratings. A Clockwork Orange by Anthony Burgess 4.38 avg rating – 556,331 ratings.
Here is the extracted data in JSON format: 1. 1. Rate this book: 1 of 5 stars 2 of 5stars 3 of 5star 4 of 5 star 5 of 5 Star 5 of 4 star 5 out of 5Star 6 of 5 Stars 7 of 5Stars 8 of 5 starred 9 of 5.
Here's how I want you to format diffs:. - - - - - -- --- -
On the Sizes of OpenAI: On the Sizing of the Size of the OpenAI. The title of this article is "On the sizes of the openAI.
To make every user a "power user" is to make every users a " power user. The potential utility of LLM is even higher for non-experts than for experts.
In Bash, the "$@" special parameter expands to all the positional parameters passed to a script or function. This includes all the arguments that have not been assigned to any other variable.
Iperf is a tool that allows you to test the network performance of a server. You can install iperf using your system's package manager. You will need to know the IP address or hostname of the server.
The command i r is used to display the current values of the CPU registers. The equivalent command in LLDB is simply register read or reg read for short.
The most straightforward way is to use the frame variable command with the -L flag, which shows the locations of the variable's data. The find command is used to search for files in a directory hierarchy based on different criteria.
Mv is the command that will be executed by the new Bash shell for each file found. $0 is a reference to the first argument passed to the shell.
How to print a.ps (PostScript) file directly to a printer using the lpr command on macOS 13. Not all printers can directly interpret PostScript files.
If your printer is directly outputting the text of the.ps file instead of rendering the PostScript content, it might be treating the input as plain text. To ensure the printer recognizes the file as PostScript, you should ensure that the correct content type is set.
Using -o raw tells the printer to treat the file as raw data, bypassing any processing or interpretation by the printer. If the file is sent as-is, there is no risk of the content being altered or formatted incorrectly.
To make it work, you need to use the same code as the previous version. This means that the original version of the document will not work.
The ~ operator in Python is used for bitwise inversion (bitwise NOT) operations. This operator flips the bits of an integer, changing all 0 bits to 1 and all 1 bits to 0.
The error message "zsh no matches found" typically occurs when you try to use a wildcard in a command and Zsh doesn't find any files or directories that match the pattern. Zsh might interpret the wildcard locally before sending it to the remote server, causing the error.
These steps should help resolve the issue of Zsh not finding matches for your remote wildcard transfers. Use the style attribute to change the size of the letter.
I want it to look like a fancy book where the text wraps around O. If 60px or 2em is too big or too small, you can adjust the number until it looks right.
Programs that help you complete some task, and then be immediately discarded. In these cases, where I don't care at all about the quality of the code, I now almost exclusively use LLMs to write them for me.
This script reads the file ct.txt into a pandas DataFrame and sorts the values based on the frequency. Then, it calculates the log10 of the frequency to achieve a log scale. Finally, it plots the data using matplotlib.
To concatenate multiple CSV files in a directory into a single dictionary in Python, you can use the os module to list the files in the directory and pandas to read and process the files.
If your CSV files have no headers, you can simply read each file line by line and append to a list. If everything works correctly, the data_dict dictionary will contain the concatenated data from all CSV files.
This will ensure that each row is read correctly even if individual data values contain special characters or if there are quoted values in your CSV. Here's how you can read the files using the csv module and concatenate them.
Use of the OpenAI API to generate the text and save it to the specified path. The generated audio files will be named sequentially as audio_0000.mp3, audio_000.mp2, audio-1000.
A Python function that reads a JSONL (JSON Lines) file and extracts the "text" value from each line. This function assumes that the input file is properly formatted with one JSON object per line.
The function will return a list of strings, where each string is the "text" value extracted from the JSON object on each line. Use the following dependencies to build the function.
If you're using an older edition of Rust, you might need to include the extern crate statements. Your Rust code should then compile without any unresolved import errors.
In this article, we show how to use a text editor to help you with reading comprehension and vocabulary. We also show how you can use the text editor's built-in search function.
I apologize for the confusion. The code is written in Rust. The function returns a vector of vectors, where each inner vector is the byte-pair encoded text.
Here's an example of how you can do this in bash. This script uses wget and unzip, which may not be installed by default on your system.
This script will attempt to download and extract over 23,000 files. If the server instead returns a 200 OK status with an error page, you would need to check the contents of the file to determine if the download was successful.
Git Large File Storage (LFS) is an open-source Git extension for versioning large files. To install Git LFS, you can follow these steps based on your operating system.
Use the following script to print out a list of URLs. You only need to print the URLs once. Use the following code to print a list.
To clone a Git repository with LFS without downloading the actual LFS files, you can use the GIT_LFS_SKIP_SMUDGE=1 environment variable. You could add error checking code to handle these cases if needed.
The process_parquet_files function reads a list of file names, then uses a ThreadPoolExecutor to download and process each file in parallel.
The number of concurrent downloads is controlled by the numworkers parameter. The download_and filter function downloads a file, loads it into a DataFrame, and writes it back to a file.
If an empty list is considered as "empty" for your use case, you should adjust the condition to check for an emptyList. If you want to remove or drop the 'content' column from your DataFrame after filtering, you can use the drop function in pandas.
I wanted to create an image of a square with 6 sides. I wanted to make it look like a picture of a pentagon. I decided to use a picture taken from the internet.
This is a 2d image where pixels are either light or dark. Each face is made of two triangles. If it's light I want a small square at that location, and if it's dark I want no square atthat location. Write a python program to do this.
The generate_cube function gives the vertices of a cube and then provides the indices that form the cube's faces. For each light pixel, we generate the cube’s vertices and then append the generated triangles to our STL data.
If you want to make more than one image, you need to use a different type of image. This is a simple way to make a larger image.
You can use the product function from itertools to compute the outer combination (or outer product) of a list with itself. Adjacent light pixels are merged into larger blocks, reducing the number of generated faces.
Here's a corrected version of your docker-compose.yml. Make sure all necessary environment variables are properly configured for your application's needs.
If you want to run your own version of Docker, you need to run it in the correct order. You can run your version of the system in the following order:
These are your primary tools for managing and interacting with your Docker containers using Docker Compose. If you run into any specific issues, feel free to ask!
Make sure your Python environment is compatible with the version of cryptography you are trying to install. Use a virtual environment to help avoid conflicts with packages installed globally.
This issue often arises due to several common causes, such as incompatible Python or package versions, issues with the pip installation, or missing system dependencies. Here's how you can address this problem.
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You can find the number of a elements within a specific <a> by using the find_all() method from BeautifulSoup. The extracted texts are stored in a list of lists, where each sublist corresponds to a <:ul> ; tag.
In this code snippet, we first find all the <ul> tags. Then, we use the find() method to find the tag with a specific id.
In bash every second write the memory usage and average CPU usage to a file. Then, we use a list comprehension to filter the <ul> tags to only those where the previous element was an <:h3.
The vmstat 1 2 command takes two samples, one second apart. The $15 field of the output gives us the CPU idle time. We use awk to extract the used memory from the result.
The open_clip model can be used to classify images against prompts. It can also be used by a web service that classifies images against given prompts.
You need Python and the FastAPI package to run the app. You can test the app by running it on your localhost account. Use the following steps to get started.
This page includes a list of the images that have been uploaded to the site.
This is a new version of the popular FastAPI service. The new version uses a new, more powerful, version of FastAPI. The old version used a different version of this service.
The new version of the FastAPI app lets you send multiple images at once. The images are sent as a set of strings, rather than as individual files.
This tool can be used to send a PIL image to a web browser. It uses the open_clip model to create a series of strings.
This approach provides flexibility for applications where images are manipulated or generated within the program, eliminating the need for temporary storage on disk before transmission. This is particularly useful in dynamic image processing applications or when handling sensitive data that should not be written to disk.
There are thousands, if not millions, of people who know the answers to any electronics question I might have. And so that means the language models probably have the answer too. And it's happy to spoon-feed me the answers so I can have the fun I want without fighting with the details.
The pitch determines the spacing between the drilled holes on the PCB. It also affects the spacing of the surface pads. Mismatched pitch can lead to assembly errors or poor electrical connections.
A standard 16MHz crystal refers to a quartz crystal oscillator that vibrates at a frequency of 16 million cycles per second. Quartz crystals are used in electronic circuits to generate precise and stable clock signals.
This page includes information on how to buy a copy of the latest issue of The Wall Street Journal. Use the weekly Newsquiz to test your knowledge of stories you saw on this page.
Use the "Add to" button to add a new project to the list. Click the "Library" button on the right side of the page to add the new project. Click "Add" to the right of the project to add it to the "Lists" section. Click on the "Bold" button at the bottom of the screen to add to the project.
The standard hole diameter for through-hole components can vary based on the type and size of the component leads. The IPC provides standards for hole sizes.
Use an adapter board specifically designed to convert 0.05-inch spacing to 0.1-inch. Soldering Wires to each pin is more manual and requires careful soldering to avoid short circuits.
An SSOP to DIP adapter can be used to connect a LoRa chip to a breadboard. The board converts a 0.05-inch spaced chip to 0.1-inch header.
Use a fine-tipped soldering iron to avoid bridging. Use a multimeter to verify continuity between the LoRa chip and the header pins.
Icut a step-by-step guide to help you solder an SSOP part onto an adapter board. The process is similar to that of making a soldering iron.
The number "681" on a capacitor typically indicates its capacitance in picofarads (pF) The solder should flow onto the pins and pads, forming clean joints.
The first two digits, "10," represent the significant figures. The third digit, "1," represents the multiplier. A capacitor marked "681" has a capacitance of 680 picofarads.
The 1.44 MB of space is the total user-accessible space, which is already factoring in the space used for the formatting and error correction.
Converting from Python to C is something I'm sure I could do in an hour or two. But there's exactly one standard Python->C calling convention. So I'll just ask the LLM to do it for me.
Here's the equivalent function in Rust using ndarray, byteorder, and walkdir crates. The nd array crate is used to handle multi-dimensional arrays, byte order crate is for reading byte data, and the walkdir crate is to read files from the directory.
This script opens the file a.out, reads its content, and then uses a. pool of 128 worker processes to run the process_file function on different parts of the. data. Note that you will need to add these crates to your Cargo.toml file.
This script assumes that the file a.out and the generated files are executable and that they produce meaningful output. The process_file function modifies the data at each index, writes it to a temporary file, executes it, reads the output, and returns it.
Remember to install the requests library if you have not already done so. You should keep your API key secret. Don't publish it in publicly accessible places like GitHub, and so forth.
Today's models still aren't quite good enough to beat me at this task in most cases, but they're getting close. Every once and a while I'll get a nice surprise when the LLM fixes a bug that I know would have been a nightmare to track down.
I made 30% more LLM queries in 2024 compared to 2023 through the web interface. I fully expect that my use of these models will continue to grow in the future. I don't think it makes sense to write off LLM because you can construct a task they can't solve.
Programmers already have a good understanding that something can be useful for different purposes. Want to write an operating system? Maybe you should use C instead of Python. Language models are exactly the same. They operate at a very high level of abstraction.
Five years ago, the best an LLM could do was write a plausibly-English sounding paragraph. Their practical utility was exactly zero. Today, they've improved my productivity at the programming aspects of my job by at least 50% on the average project.
I don't know whether to be excited or afraid. But I suspect that there are other people out there who could benefit from them as well. We'll see what the next five years bring.