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448
Yay I made an in memory vector DB in pure golang, check it out here https://github.com/takara-ai/serverlessVector
AI & ML interests
None defined yet.
takarajordan
posted
an
update
about 1 month ago
takarajordan
posted
an
update
about 1 month ago
Post
2625
Are we really back to storing access tokens in plain text again?
{
"mcpServers": {
"hf-mcp-server": {
"url": "https://huggingface.co/mcp",
"headers": {
"Authorization": "Bearer <YOUR_HF_TOKEN>"
}
}
}
}
- 3 replies
takarajordan
posted
an
update
2 months ago
Post
3038
I'm currently looking into what makes a scientific paper more popular than others on a platform like Hugging Face. I conducted a huge array of tests, content length, time based information even semantic feature extraction to get to some sort of answer around...
What actually drives popularity of these papers, why do some papers get zero upvotes and why do some get thousands?
The answer is absolutely nothing. Yes that's right. Nothing about the actual paper itself drives popularity, the paper's popularity is driven by external factors like it's authors, external marketing and others.
So next time you see a research paper with a lot of upvotes, just remember it's not because of the efforts of the authors. Remain objective.
What actually drives popularity of these papers, why do some papers get zero upvotes and why do some get thousands?
The answer is absolutely nothing. Yes that's right. Nothing about the actual paper itself drives popularity, the paper's popularity is driven by external factors like it's authors, external marketing and others.
So next time you see a research paper with a lot of upvotes, just remember it's not because of the efforts of the authors. Remain objective.
takarajordan
posted
an
update
2 months ago
Post
246
cron + LLM api is cracked
- 2 replies
takarajordan
posted
an
update
3 months ago
Post
284
What do you all actually think about the open source OpenAI models? Are they legitimately any good or are they hype?
- 3 replies
takarajordan
posted
an
update
5 months ago
Post
388
Cool to see the new model lightonai/Reason-ModernColBERT
Made with late interaction I'd love to recreate the dataset to see a proper apache 2.0 version!
Made with late interaction I'd love to recreate the dataset to see a proper apache 2.0 version!
takarajordan
posted
an
update
7 months ago
Post
645
🎌 Two months in, https://github.com/takara-ai/go-attention has passed 429 stars on GitHub.
We built this library at takara.ai to bring attention mechanisms and transformer layers to Go — in a form that's lightweight, clean, and dependency-free.
We’re proud to say that every part of this project reflects what we set out to do.
- Pure Go — no external dependencies, built entirely on the Go standard library
- Core support for DotProductAttention and MultiHeadAttention
- Full transformer layers with LayerNorm, feed-forward networks, and residual connections
- Designed for edge, embedded, and real-time environments where simplicity and performance matter
Thank you to everyone who has supported this so far — the stars, forks, and feedback mean a lot.
We built this library at takara.ai to bring attention mechanisms and transformer layers to Go — in a form that's lightweight, clean, and dependency-free.
We’re proud to say that every part of this project reflects what we set out to do.
- Pure Go — no external dependencies, built entirely on the Go standard library
- Core support for DotProductAttention and MultiHeadAttention
- Full transformer layers with LayerNorm, feed-forward networks, and residual connections
- Designed for edge, embedded, and real-time environments where simplicity and performance matter
Thank you to everyone who has supported this so far — the stars, forks, and feedback mean a lot.
-
- 4 replies
takarajordan
posted
an
update
7 months ago
Post
1597
AI research over coffee ☕️
No abstracts, just bullet points.
Start your day here: https://tldr.takara.ai
No abstracts, just bullet points.
Start your day here: https://tldr.takara.ai
- 1 reply
takarajordan
posted
an
update
7 months ago
Post
1881
Takara takes 3rd place in the {tech:munich} AI hackathon with Fudeno!
A little over 2 weeks ago @aldigobbler and I set out to create the largest MultiModal SVG dataset ever created, we succeeded in this and when I was in Munich, Germany I took it one step further and made an entire app with it!
We fine-tuned Mistral Small, made a Next.JS application and blew some minds, taking 3rd place out of over 100 hackers. So cool!
If you want to see the dataset, please see below.
takara-ai/fudeno-instruct-4M
A little over 2 weeks ago @aldigobbler and I set out to create the largest MultiModal SVG dataset ever created, we succeeded in this and when I was in Munich, Germany I took it one step further and made an entire app with it!
We fine-tuned Mistral Small, made a Next.JS application and blew some minds, taking 3rd place out of over 100 hackers. So cool!
If you want to see the dataset, please see below.
takara-ai/fudeno-instruct-4M
takarajordan
posted
an
update
11 months ago
Post
2402
I made an RSS feed for HuggingFace Daily Papers!! 🤗
Just Subscribe here: https://papers.takara.ai/api/feed
It updates every 24 hours, completely written as a serverless go script with a Redis cache (to avoid hitting HF all the time).
I'm open sourcing the code, you can check out my repo and deploy it on Vercel extremely easily!
https://github.com/404missinglink/HF-Daily-Papers-Feeds
thanks to @John6666 @p3nGu1nZz for your early support
Just Subscribe here: https://papers.takara.ai/api/feed
It updates every 24 hours, completely written as a serverless go script with a Redis cache (to avoid hitting HF all the time).
I'm open sourcing the code, you can check out my repo and deploy it on Vercel extremely easily!
https://github.com/404missinglink/HF-Daily-Papers-Feeds
thanks to @John6666 @p3nGu1nZz for your early support
- 1 reply
takarajordan
posted
an
update
11 months ago
Post
2513
I'm super excited to release my first open-source text dataset:
WorldScenario 20K is a novel dataset of 20,000 synthetically generated multi-stakeholder scenarios designed to simulate real-world decision-making processes. Each scenario explores a unique environmental, societal, or economic issue.
I used the brand new meta-llama/Llama-3.3-70B-Instruct model to generate this dataset and I put the dataset through some post processing to clean and evaluate the dataset for diversity.
I'd appreciate some feedback and thoughts on my new release! Thanks!
takarajordan/WorldScenario_20K
WorldScenario 20K is a novel dataset of 20,000 synthetically generated multi-stakeholder scenarios designed to simulate real-world decision-making processes. Each scenario explores a unique environmental, societal, or economic issue.
I used the brand new meta-llama/Llama-3.3-70B-Instruct model to generate this dataset and I put the dataset through some post processing to clean and evaluate the dataset for diversity.
I'd appreciate some feedback and thoughts on my new release! Thanks!
takarajordan/WorldScenario_20K
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- 8 replies
takarajordan
posted
an
update
11 months ago
Post
1212
I'm not sure why I haven't done this already!
I just made a space to count and visualize tokens for Diffusion models, no more guesswork! It's super fast too.
Check it out here and try out your prompts: takarajordan/DiffusionTokenizer
Uses these tokenizers below:
openai/clip-vit-large-patch14
google/t5-v1_1-xxl
I just made a space to count and visualize tokens for Diffusion models, no more guesswork! It's super fast too.
Check it out here and try out your prompts: takarajordan/DiffusionTokenizer
Uses these tokenizers below:
openai/clip-vit-large-patch14
google/t5-v1_1-xxl
takarajordan
posted
an
update
11 months ago
Post
1128
First post here goes!
takarajordan/CineDiffusion
Super excited to announce CineDiffusion🎥, it creates images up to 4.2 Megapixels in Cinematic ultrawide formats like:
- 2.39:1 (Modern Widescreen)
- 2.76:1 (Ultra Panavision 70)
- 3.00:1 (Experimental Ultra-wide)
- 4.00:1 (Polyvision)
- 2.55:1 (CinemaScope)
- 2.20:1 (Todd-AO)
More to come soon!!
Thanks to @John6666 and @Resoldjew for your early support <3
And thanks to the team at ShuttleAI for their brand new Shuttle-3 model, what an amazing job.
shuttleai/shuttle-3-diffusion
takarajordan/CineDiffusion
Super excited to announce CineDiffusion🎥, it creates images up to 4.2 Megapixels in Cinematic ultrawide formats like:
- 2.39:1 (Modern Widescreen)
- 2.76:1 (Ultra Panavision 70)
- 3.00:1 (Experimental Ultra-wide)
- 4.00:1 (Polyvision)
- 2.55:1 (CinemaScope)
- 2.20:1 (Todd-AO)
More to come soon!!
Thanks to @John6666 and @Resoldjew for your early support <3
And thanks to the team at ShuttleAI for their brand new Shuttle-3 model, what an amazing job.
shuttleai/shuttle-3-diffusion