BlingFire
autocomplete
| BlingFire | autocomplete | |
|---|---|---|
| 2 | 164 | |
| 1,781 | 24,274 | |
| 0.3% | 0.1% | |
| 3.6 | 9.6 | |
| 6 months ago | 2 days ago | |
| C++ | TypeScript | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
BlingFire
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[D] SentencePiece, WordPiece, BPE... Which tokenizer is the best one?
SentencePiece -> implementation of some algorithms (there are several others, https://github.com/microsoft/BlingFire https://github.com/glample/fastBPE https://github.com/huggingface/tokenizers )
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Ask HN: Who is hiring? (March 2021)
• Develop the best technology to bring deep learning solutions to unprecedented scale, for example we built the world's fastest tokenizer. [https://github.com/microsoft/BlingFire]
autocomplete
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Fig Is Sunsetting
Having contributed to the Fig autocomplete specs, I find this sad. The Amazon product Fig was built into basically works as replacement, which is good. Still, the core value of this product are the open-source autocomplete specs: https://github.com/withfig/autocomplete. What's going to happen to that? It looks like they are still using it in the Amazon product. It should definitely be possible for an open-source re-implementation of the Fig UI to use those specs. There is a lot of knowledge encoded in there!
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Top Free Utility Mac Apps You Aren’t Using
8. Fig
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Ask HN: Alternatives to fig.io as it has signups disabled?
Fig is awesome but with signups blocked[1] for 2+mo already it's also as good as dead ¯\_(ツ)_/¯
* [1]: https://github.com/withfig/autocomplete/issues/2068
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Show HN: Inshellisense – IDE style shell autocomplete
https://github.com/withfig/autocomplete is it this?
- Fig
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Show HN: Whiz – A copilot for your command line
How is this different than https://fig.io/?
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Boost DX, Enhance UX, and Skyrocket Profits! Dive into a sub-50ms world with Edge Feature Flags 🚀
AWS CloudWatch Evidently The worst. No comment. AWS seems to perpetually lack a good DX for developers. It appears that they don't recognize or continually undervalue the importance of roles other than engineers, such as Product Managers or Designers. Very disappointing. However, AWS has recently acquired Fig, so looks like they're now pursuing an acquisition strategy instead. Let's see how it turns it out, and let's hope they don't ruin Fig, since it's such an useful tool.
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Ask HN: What are some well-designed websites?
slightly tangential, but where do people get awesome landing pages like linear(https://fig.io/. has similar landing page) etc. Do they build them in-house or buy templates somewhere? Many of the recently launched YC companies have awesome landing pages. eg. https://automorphic.ai/,
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Fig Has Joined AWS
I love this product, have contributed several times to it, and I'm a little torn. One thing I am thinking about now, is that the completion specs are MIT-licensed, and it should be possible to use them to re-implement a basic open-source version of the autocompletion product... https://github.com/withfig/autocomplete
What are some alternatives?
tokenizers - 💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
ohmyzsh - 🙃 A delightful community-driven (with 2,300+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python, etc), 140+ themes to spice up your morning, and an auto-update tool so that makes it easy to keep up with the latest updates from the community.
Mattermost - Mattermost is an open source platform for secure collaboration across the entire software development lifecycle..
fzf-tab - Replace zsh's default completion selection menu with fzf!
OpenKP - Automatically extracting keyphrases that are salient to the document meanings is an essential step to semantic document understanding. An effective keyphrase extraction (KPE) system can benefit a wide range of natural language processing and information retrieval tasks. Recent neural methods formulate the task as a document-to-keyphrase sequence-to-sequence task. These seq2seq learning models have shown promising results compared to previous KPE systems The recent progress in neural KPE is mostly observed in documents originating from the scientific domain. In real-world scenarios, most potential applications of KPE deal with diverse documents originating from sparse sources. These documents are unlikely to include the structure, prose and be as well written as scientific papers. They often include a much diverse document structure and reside in various domains whose contents target much wider audiences than scientists. To encourage the research community to develop a powerful neural m
Warp - Warp is a modern, Rust-based terminal with AI built in so you and your team can build great software, faster.
sgr - sgr (command line client for Splitgraph) and the splitgraph Python library
starship - ☄🌌️ The minimal, blazing-fast, and infinitely customizable prompt for any shell!
python-fake-data-producer-for-apache-kafka - The Python fake data producer for Apache Kafka® is a complete demo app allowing you to quickly produce JSON fake streaming datasets and push it to an Apache Kafka topic.
hyperterm - A terminal built on web technologies
fargate-game-servers - This repository contains an example solution on how to scale a fleet of game servers on AWS Fargate on Elastic Container Service and route players to game sessions using a Serverless backend. Game Server data is stored in ElastiCache Redis. All resources are deployed with Infrastructure as Code using CloudFormation, Serverless Application Model, Docker and bash/powershell scripts. By leveraging AWS Fargate for your game servers you don't need to manage the underlying virtual machines.
zsh-autocomplete - 🤖 Real-time type-ahead completion for Zsh. Asynchronous find-as-you-type autocompletion.