Show HN: Fully client-side GPT2 prediction visualizer https://bit.ly/45TSJHe

Show HN: Fully client-side GPT2 prediction visualizer https://bit.ly/45HJM4g September 5, 2023 at 11:42PM

Show HN: Simple passwordless authentication for your website https://bit.ly/45APSU3

Show HN: Simple passwordless authentication for your website Solo founder here - built a passwordless authentication service after getting frustrated with the very high pricing and lack of customizability, easy passwordless authentication on existing solutions. Check it out here and let me know what you think! https://bit.ly/45FSkbS September 5, 2023 at 08:47AM

Show HN: Chalk.ist – Create beautiful images of your source code https://bit.ly/3R9hL1c

Show HN: Chalk.ist – Create beautiful images of your source code https://bit.ly/3MevSwk September 5, 2023 at 07:54AM

Show HN: Subsidian – Visualize a Substack archive in Obsidian graph view https://bit.ly/45TuclN

Show HN: Subsidian – Visualize a Substack archive in Obsidian graph view https://bit.ly/3Z66TCU September 4, 2023 at 03:08PM

Show HN: Keep – GitHub Actions for your monitoring tools https://bit.ly/48e39DV

Show HN: Keep – GitHub Actions for your monitoring tools Hi Hacker News! Shahar and Tal from Keep here. A few months ago, we introduced here at HN ( https://bit.ly/3EcwLE1 ) Keep as an “open source alerting CLI” and got some interesting feedback - mainly around UI, automation, and supporting more tools. We were VERY early back then, and we understood that although the current DX around creating alerts is not great, it's not that critical and developers don’t need another tool just for that. But we did find something else. While talking to developers and devops, we found that a lot of companies use many tools that generate alerts - from Cloudwatch, Prometheus, Grafana, and Datadog to tools such as Zabbix or Nagios. We definitely agree consolidation in the observability space is a real thing, but while talking to those companies we feel that there are still real use cases for having more than one tool (and for example, according to Grafana’s 2023 observability survey, 52% of the companies uses more than 6 observability tools https://bit.ly/47Ysbqh ). So we that in mind, we rebuilt Keep with a simple mindset: (1) Integrate with every tool that triggers alerts - it can be either pushing alerts to Keep via webhooks or routing policies or Keep to pull alerts via the tools API. (2) Create a simple abstraction layer to run workflows on top of these alerts. (3) Maintain a great developer experience - open source, API-first, workflows as code and generally having a developer mindset while building Keep. During the time we rebuilt Keep, Datadog released their workflow automation tool ( https://bit.ly/3L75FBC ) which led us to the understanding that's exactly what we solve - but for everyone who uses tools other than Datadog. A short demo of Keep with a simple use case: https://www.youtube.com/watch?v=FPMRCZM8ZYg You can try it yourself by signing into https://bit.ly/3Nipgk6 Like always - we invite you to try Keep and we are eager to hear any feedback. https://bit.ly/3IrvGuF September 4, 2023 at 04:15PM

Show HN: Recognize license plates using fine-tuned yolov8, OCR and IP camera https://bit.ly/46fACfp

Show HN: Recognize license plates using fine-tuned yolov8, OCR and IP camera Hey, just a work related project I made, which could be open sourced :D If you're looking for an example on how to use/fine-tune yolov8, I feel like taking a look at this repo and reading the README could help you get up to speed (also linked some nice refs)! This is actually a full rewrite of a proprietary project I made (and documented on my site) like a year ago, will do some finishing touches (write blog post about it, mark the old version deprecated, record a tutorial on how to set it up on an Ubuntu server, etc, etc) in the following month, but felt like sharing it now, cuz I consider it done The only proprietary part is the client, which receives the images and does stuff with db (has to interact with internal APIs, so there's no reason to make it oss anyways). Also, the client contains only the business logic, all of the fun ai/web server stuff is fully open under AGPL-3.0 (and an example client without the business logic is available ... in rust btw xdd). https://bit.ly/3qYiJme September 4, 2023 at 08:56PM

Show HN: TTop – System monitoring tool with historical data, triggers and TUI https://bit.ly/3qZ9Ngl

Show HN: TTop – System monitoring tool with historical data, triggers and TUI It is not top/htop replacement because of historical snapshots which can help you to find problems back in time https://bit.ly/44G50y9 September 4, 2023 at 04:50PM

Show HN: finetune LLMs via the Finetuning Hub https://bit.ly/3PnIQMB

Show HN: finetune LLMs via the Finetuning Hub Hi HN community, I have been working on benchmarking publicly available LLMs these past couple of weeks. More precisely, I am interested on the finetuning piece since a lot of businesses are starting to entertain the idea of self-hosting LLMs trained on their proprietary data rather than relying on third party APIs. To this point, I am tracking the following 4 pillars of evaluation that businesses are typically look into: - Performance - Time to train an LLM - Cost to train an LLM - Inference (throughput / latency / cost per token) For each LLM, my aim is to benchmark them for popular tasks, i.e., classification and summarization. Moreover, I would like to compare them against each other. So far, I have benchmarked Flan-T5-Large, Falcon-7B and RedPajama and have found them to be very efficient in low-data situations, i.e., when there are very few annotated samples. Llama2-7B/13B and Writer’s Palmyra are in the pipeline. But there’s so many LLMs out there! In case this work interests you, would be great to join forces. GitHub repo attached — feedback is always welcome :) Happy hacking! https://bit.ly/3ElU8uG September 4, 2023 at 04:16PM

Show HN: Rapidgzip – Truly Parallel Gzip Decompression with 10 GB/s https://bit.ly/3PoJJVi

Show HN: Rapidgzip – Truly Parallel Gzip Decompression with 10 GB/s I have posted a much earlier version of this over a year ago [0]. Since then a lot has changed. Obviously, the name has changed. This happened for the paper publication [1]. I have also optimized the speed, integrated ISA-L for special cases, limited the compression-ratio-dependent maximum memory consumption, and finally added parallelized CRC32 computation, which adds ~5% overhead no matter the number of cores used. At this point, I am leaning towards calling it production-ready although there are still many ideas for improvements. Redoing the benchmarks of the older Show HN, would look like this: time pigz -d -c 4GiB-base64.gz | wc -c # real ~13.4 s -> ~320 MB/s time rapidgzip -d -c 4GiB-base64.gz | wc -c # real ~1.26 s -> ~3.4 GB/s However, at this point, the piping itself becomes a problem. Rapidgzip is actually slightly faster than cat when comparing the piped bandwidth! E.g., compare these additional benchmarks: time cat 4GiB-base64.gz | wc -c # real ~1.06 s -> ~3.1 GB/s time fcat 4GiB-base64.gz | wc -c # real ~0.41 s -> ~8.0 GB/s time rapidgzip -o /dev/null -d 4GiB-base64.gz # real ~0.68 s -> ~6.5 GB/s fcat is an alternative cat implementation that uses vmsplice to speed up piping. According to the ReadMe it currently is broken, but it works fine on my system and piping it to md5sum yields consistent results [2]. So, at this point, I/O and actually also allocations have become a limiting factor and if you want full speed, you would have to interface with the rapidgzip library interface directly (in C++ or via the Python bindings) and process the decompressed data in memory. The project ReadMe contains further benchmarks with Silesia and FASTQ data and scaling up to 128 cores, for which rapidgzip achieves 12 GB/s for Silesia and 24 GB/s when an index has been created with --export-index and is used with --import-index. It can also be tested with ratarmount 0.14.0, which now uses rapidgzip as a backend by default for .gz and .tar.gz files [3]. [0] https://bit.ly/3P3MRT2 [1] https://bit.ly/3Evkvhz [2] https://bit.ly/3EItoot [3] https://bit.ly/3hZj1Ba https://bit.ly/3qX04Hi September 4, 2023 at 09:29AM

Show HN: FileSamplesHub – Free sample files to all your testing purposes https://bit.ly/47XFJlT

Show HN: FileSamplesHub – Free sample files to all your testing purposes https://bit.ly/47WLznF September 4, 2023 at 09:18AM

Show HN: The simplest way to validate your idea https://bit.ly/3LavZed

Show HN: The simplest way to validate your idea Real idea (The Facts Clock): https://bit.ly/45Birke https://bit.ly/3sDRfCL September 4, 2023 at 04:44AM

Show HN: MonoDevelop https://bit.ly/3PmczFQ

Show HN: MonoDevelop https://bit.ly/3Emznie September 4, 2023 at 04:51AM

Show HN: FeedsBot – A Meower bot that posts RSS feed updates to groupchats https://bit.ly/3PoH3a8

Show HN: FeedsBot – A Meower bot that posts RSS feed updates to groupchats Hi, HN! I made this awhile back as a Meower[1] bot that posts RSS feed updates to groupchats, and reads RSS feeds, powered by Extractus' Feed Extractor[2][3]. My friend's groupchat uses this bot to post updates to his blog, and he says that it has been working out great. Looking forward to your feedback and suggestions! [1]: https://bit.ly/3L76ASK [2]: https://bit.ly/3Z5rffW [3]: https://bit.ly/3Z4ibaN https://bit.ly/3PoxurO September 4, 2023 at 12:33AM

Show HN: A gem that shows jobs right in the command line https://bit.ly/3sFs8Qd

Show HN: A gem that shows jobs right in the command line It scrapes Ruby/Ruby on Rails jobs from six sites: Gorails, Weworkremotely, Ruby on Remote, Ruby on Rails jobs, Rails Hotwire Jobs, WeAreHiring, and displays them right in your terminal! The scraper lives on: https://bit.ly/3R6iDnh Please comment other sites that you use to look up Ruby/ROR jobs! https://bit.ly/3r2Qq5W September 3, 2023 at 06:40PM

Show HN: Command line query for all your unified log data https://bit.ly/3P0SJyE

Show HN: Command line query for all your unified log data https://bit.ly/3OZJcYx September 3, 2023 at 03:20PM

Show HN: Extract RSS feed from almost anything https://bit.ly/3L5P3u0

Show HN: Extract RSS feed from almost anything Howdy! RSSfeedASAP scratches my own itch. I run a regional podcasting directory which gets dozens of messy submission for podcasts. Often they don't even include an xml file and me being a good samaritan I sometimes do the manual work and find it myself. I got tired of that manual work and decided to build a microapp. RSSfeedASAP is this app and I decided to release it in case someone else finds any use in it. https://bit.ly/3L4KNLq September 3, 2023 at 04:37PM

Show HN: You wanted SMS, you've got it (HN community is awesome) https://bit.ly/3r6p2UC

Show HN: You wanted SMS, you've got it (HN community is awesome) The HN Community is awesome! Since posting in April about my frustration with PagerDuty and why I built All Quiet, I received many direct emails with feature requests or product roadmap questions. Out of this eager engagement we could integrate a bunch of cool new features: Since my post in April regarding my frustrations with PagerDuty and my rationale behind creating All Quiet, I've received many direct emails containing feature requests and questions about our product roadmap. Thanks to this awesome engagement, we've been able to integrate several fantastic new features: SMS & Voice Calls: ------------------ Initially, we weren't convinced that this would align with our product strategy. After all, why opt for SMS when there are push notifications? However, the demand for this feature was undeniable, so we went ahead and built it! https://bit.ly/3EpOA2m... Do Not Disturb Overrides: ------------------ We've rolled out a comprehensive guide for Android app users, ensuring they can seamlessly configure their DnD overrides. https://bit.ly/3EsNP8o... We're in the queue, awaiting Apple's green light for the "Critical Alert" entitlement. We've already coded the support for this in our iOS app. Schedules & Rotations: ------------------ This was a top request from the community — tools to manage rotations and schedules. We collaborated directly with teams that asked for this feature. The experience was genuinely collaborative, and we're immensely grateful to the teams that helped shape this functionality. https://bit.ly/3Em0ZUX... Login through Google & Microsoft: ------------------ Given that many teams use Google or Microsoft for authentication, it was only logical to incorporate these platforms as login providers. https://bit.ly/3P41WG9 September 3, 2023 at 09:26AM

Show HN: Cross-platform dotfiles manager written in Rust https://bit.ly/3qWERgC

Show HN: Cross-platform dotfiles manager written in Rust https://bit.ly/33UM8SR September 3, 2023 at 08:03AM

Show HN: A .bit gateway for resolving ipfs:// to https:// https://bit.ly/45Vtncg

Show HN: A .bit gateway for resolving ipfs:// to https:// bit.site dynamically captures all requests to *.bit.site, automatically resolving the IPFS/IPNS/Skynet content hashes for the corresponding .bit account records. It returns the relevant static content via HTTPS, enabling users to access decentralized networks with zero configuration on modern browsers. At the same time, we provide global CDN acceleration, striving to enhance the availability of decentralized content. https://bit.ly/3YYIxLv September 2, 2023 at 04:30PM

Show HN: Modular Diffusion – A modular Python library for diffusion models https://bit.ly/3Z3KqGX

Show HN: Modular Diffusion – A modular Python library for diffusion models Hello everyone! I've been working on this project for a few months as part of my thesis in Machine Learning. It's meant to be a library that provides an easy-to-use but flexible API to design and train Diffusion Models. I decided to make it because I wanted to quickly prototype a Diffusion Model but there were no good tools to do it with. I think it really can help people prototype their own Diffusion Models a lot faster and only in a few lines of code. The base idea is to have a Model class that takes different modules corresponding to the different aspects of the Diffusion Model process (noise schedule, noise type, denoising network, loss function, guidance, etc.) and allow the user to mix and match different modules to achieve different results. The library ships with a bunch of prebuilt modules and the plan is to add many more. I also made it super easy to implement your own modules, you just need to extend from one of the base classes available. Contrary to HuggingFace Diffusers, this library is focused on designing and training your own Diffusion Models rather than finetuning pretrained ones (although this is possible). I would really appreciate your feedback. https://bit.ly/45yDqUU September 2, 2023 at 03:16PM