warangal

9 ms·

1.
by warangal 6mo ago
VITS is such a cool model (and paper), fast, minimal, trainable. Meta took it to extreme for about 1000 languges. It seems like you have been working on this application for sometime, i will go through your code , but could you provide some
2.
by warangal 6mo ago
I may be wrong here, but blog-post seems AI written, with repetition of sequences like "the inference pipeline was rebuilt using architecture-aware fused kernels, optimized scheduling, and dis-aggregated serving". I don't kn
3.
by warangal 7mo ago
pretty cool work! Though it leaves me wondering if coreboot/bios code can directly interface with thermal-management and battery controller , shouldn't it be feasible to improve upon battery life by exposing some interface to OS,
4.
by warangal 7mo ago
I was also reading through lobsters Memory management, which (i think) currently implements "borrow first" semantics, to do away with a lot of run-time reference counting logic, which i think is a very practical approach. Also i h
5.
by warangal 9mo ago
How do you market it, through social-media or are there dedicated channels for sharing awareness for such Mac Apps, if you don't mind sharing?
6.
by warangal 10mo ago
I work on an image search engine[0], main idea has been to preserve all the original meta-data and directory structure while allowing semantic and meta-data search from a single interface. All meta-data is stored in a single json file, wit
7.
by warangal 10mo ago
Currently (Semantic) ML model is the weakest (minorly fine-tuned) ViT B/32 variant, and more like acting as a placeholder i.e very easy to swap with a desired model. (DINO models have been pretty great, being trained on much cleaner an
8.
by warangal 10mo ago
Hi, Author here! I have been working on this project for quite some time now. Even though for such search engines, basic ideas remain the same i.e extracting meta-data or semantic info, and providing an interface to query it. Lots of effor
9.
Hachi: An Image Search Engine(eagledot.xyz)
152 points by warangal 10mo ago|14 comments
10.
by warangal 10mo ago
Using `zig-cc (clang)` to set a particular `LibC` version is one of the best decisions i have made, and saved me from those meaningless libC mismatch errors!
11.
by warangal 10mo ago
I know it may be not what you are looking for, but most of such models generate multiple-scale image features through an image encoder, and those can be very easily fine-tuned for a particular task, like some polygon prediction for your use
12.
by warangal 1y ago
Pretty cool project!, I have been also trying to do something similar with very limited (abstract) OPs akin to fundamental computer instructions. Just using the numpy backend for now to test theory, but neat thing is that most of complexity
13.
by warangal 1y ago
A bit tangential statement, about parakeet and other Nvidia Nemo models, i never found actual architecture implementations as pytorch/tf code, seems like all such models, are instant-ized from a binary blob making it difficult to exper
14.
by warangal 1y ago
Nice write up! It is about speeding up underlying hash-table for a `cuckoo filter` , as in false-positives are allowed, unlike data-structure like dictionary, which makes sure that false-positive rate is 0. Whenever i need to use dictionary
15.
by warangal 1y ago
Thanks for explaining it, given you are writing it from scratch it gives you a lot of control in modelling a particular feature! I did bookmark this project a few months ago but couldn't spend time to understand more about it. I wasn&#
16.
by warangal 1y ago
Are you trying to do this message passing using Nim channels ? For my use-cases, i always had to resort to just passing `pointers`, to prevent any copying, most of time i just divide the problem to use independent memory locations to write
17.
Film School Rejects Is Seeking New Ownership(filmschoolrejects.com)
1 points by warangal 2y ago|0 comments
18.
by warangal 2y ago
for images readme is at: https://github.com/eagledot/hachi/tree/main/images/readme.md with more than enough details! It is supposed to be a search engine for all modalities, for now `images` are sup
19.
by warangal 2y ago
Disclaimer: I work on such a project[0] I think a combination of CLIP and some face-recognition may solve your issues! It just takes a path to your directory, and can index all the images while preserving your folder hierarchy along with a
20.
by warangal 2y ago
Yes, trigram mainly but also bigram and/or combination of both are used generally to implement fuzzy search, zoekt also uses trigram index. But such indices depend heavily on the content being indexed, for example if ever encounter a r
21.
by warangal 2y ago
I myself have been working on a personal search engine for sometime, and one problem i faced was to have an effective fuzzy-search for all the diverse filenames/directories. All approaches i could find were based on Levenshtein distanc
22.
Malhar: Towards a fast, generic and minimal Fuzzy Search Index(eagledot.xyz)
2 points by warangal 2y ago|0 comments
23.
by warangal 2y ago
Embeddings capture a lot of semantic information based on the training data and objective function, and can be used independently for a lot of useful tasks. I used to use embeddings from the text-encoder of CLIP model, to augment the prompt
24.
by warangal 2y ago
It is a small DSL written using macros at https://github.com/mratsim/Arraymancer/blob/master/src/array... . Nim has pretty great meta-programming capabilities and arraymancer employs some cool featur
25.
by warangal 3y ago
It is quite possible B variant is not enough for some scenarios, earlier version also included the videos search, frames used for indexing were sometimes blur (not having fine-details) and these frames generally would have higher score for
26.
by warangal 3y ago
I keep forgetting to put a benchmark for a standard flickr30k like dataset! But a ballpark figure should be about 100ms per image on a quad-core CPU, i also generate an ETA during indexing and provide some meta-information to make it easy t
27.
by warangal 3y ago
I think image-encoder from CLIP (even smallest variant ViT B/32) is good enough to capture a lot of semantic information to allow natural language query once images are indexed. A lot of work actually goes into integrating with existin
28.
by warangal 3y ago
Thanks for this resource! Even though i have been able to collect enough resources for Neon/simd programming but having a proper guide is indispensable and arm official documentation doesn't make it easy in any way!
29.
by warangal 3y ago
Just wanted to say thanks for this and all other such detailed posts!. Found your blog a few weeks ago and have been going through posts running NuttX RTOS on these SBCs, but admittedly feel overwhelmed with sheer amount of information pack
30.
by warangal 3y ago
This is a very nice writeup, and clearly dictates performance benefits to be gained from using underlying hardware properly. Couple of things i noticed. ``` # calculating dot product a = np.random.randn(1,1536).astype("float32")

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