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nyuuzyou

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reacted to mitkox's post with 🔥 about 5 hours ago

My USB charger has a Blackwell GPU and 128GB RAM. What. A. Time. To. Be. Alive. People in Sofia: “It’s freezing.” Me: sitting next to 3kW of space AI heaters on my desk 👀 1x GLM-5, 2x MiniMax-M2.5, 1x Qwen3 Coder Next; all on single Aibrix/K8s cluster

reacted to danielhanchen's post with 🚀 1 day ago

We collabed with HF on showing how you can use HF Jobs and Unsloth! https://huggingface.co/blog/unsloth-jobs

replied to Tonic's post 2 days ago

🤔 Who would win ? - a fully subsidized ai lab `OR ` - 3 random students named https://hf.co/kurakurai ? demo : https://huggingface.co/spaces/Tonic/fr-on-device if you like it give the demo a little star and send a shoutout to : @MaxLSB @jddqd and @GAD-cell for absolutely obliterating the pareto frontier of the french language understanding .

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reacted to mitkox's post with 🔥 about 5 hours ago

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4934

My USB charger has a Blackwell GPU and 128GB RAM.
What. A. Time. To. Be. Alive.
People in Sofia: “It’s freezing.”
Me: sitting next to 3kW of space AI heaters on my desk 👀
1x GLM-5, 2x MiniMax-M2.5, 1x Qwen3 Coder Next; all on single Aibrix/K8s cluster

5 replies

reacted to danielhanchen's post with 🚀 1 day ago

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We collabed with HF on showing how you can use HF Jobs and Unsloth! https://huggingface.co/blog/unsloth-jobs

replied to Tonic's post 2 days ago

In short, the students won. They did so by fine-tuning LFM2. LFM2 is a foundation built by Liquid AI. Liquid AI is a $2 billion startup from MIT.

reacted to ajibawa-2023's post with 🔥 4 days ago

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JavaScript-Code-Large
ajibawa-2023/JavaScript-Code-Large

JavaScript-Code-Large is a large-scale corpus of JavaScript source code comprising around 5 million JavaScript files. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, software engineering automation, and program analysis for the JavaScript ecosystem.

By providing a high-volume, language-specific corpus, JavaScript-Code-Large enables systematic experimentation in JavaScript-focused model training, domain adaptation, and downstream code understanding tasks.

JavaScript-Code-Large addresses the need for a dedicated JavaScript-only dataset at substantial scale, enabling focused research across frontend, backend, and full-stack JavaScript environments. .

posted an update 5 days ago

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🎰 Casino Benchmark: Dataset + Space
nyuuzyou/casino-benchmark
nyuuzyou/casino-benchmark

14 models faced 1,400 simulations of heads-up Blackjack and European Roulette. Shared seeds locked identical cards and spins for each.

Key Stats:

- 14 models benchmarked
- 59,483 rows
- 35 MB compressed Parquet
- 35,000 scored decisions
- Full prompts, JSON responses, reasoning traces, latency
- Bankroll tracking from $1,000 start per run

Live leaderboard tracks bets, hits, stands, and risk management.
Gemini 3 Flash leads at +$3,396. Claude 4.5 Haiku at -$7,788.
Traces in the dataset. Leaderboard in the space.

reacted to vikhyatk's post with 🔥 10 days ago

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Just released a preview of Moondream 3! moondream/moondream3-preview

This is a 9B parameter, 2B active MoE VLM with state of the art visual reasoning capabilities.

More details in the release blog post: https://moondream.ai/blog/moondream-3-preview

3 replies

reacted to mitkox's post with 👍 15 days ago

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I just pushed Claude Code Agent Swarm with 20 coding agents on my desktop GPU workstation.

With local AI, I don’t have /fast CC switch, but I have /absurdlyfast:
- 100’499 tokens/second read, yeah 100k, not a typo | 811 tok/sec generation
- KV cache: 707’200 tokens
- Hardware: 5+ year old GPUs 4xA6K gen1; It’s not the car. It’s the driver.

Qwen3 Coder Next AWQ with cache at BF16. Scores 82.1% in C# on 29-years-in-dev codebase vs Opus 4.5 at only 57.5%. When your codebase predates Stack Overflow, you don't need the biggest model; you need the one that actually remembers Windows 95.

My current bottleneck is my 27" monitor. Can't fit all 20 Theos on screen without squinting.

3 replies

replied to ZennyKenny's post 18 days ago

SEO spam has also become a lot less noticeable. I'm hoping that the next step will be to crack down on storage and traffic abuse, and maybe that will mean more generous storage limits.

reacted to ZennyKenny's post with 😎 18 days ago

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🫠 Brutal! Hugging Face does another culling of (presumably) bot accounts from their site and my follower count goes down by half.

💀 TFW my content and models only appeal to bots. Who’s got the current best AI girlfriend app guys?

11 replies

posted an update 21 days ago

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Earlier I asked for a storage grant for some new datasets. One of those, the Google Code Archive nyuuzyou/google-code-archive, is now in trending. Thanks to Hugging Face and the community for the support. 🤗

1 reply

posted an update 23 days ago

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🏛️ Microsoft CodePlex Archive Dataset - nyuuzyou/ms-codeplex-archive

Following the strong response to the Google Code Archive nyuuzyou/google-code-archive (thanks!), this release preserves another major historical repository: the Microsoft CodePlex Archive.

CodePlex served as Microsoft’s primary open-source hosting platform from 2006 to 2017. This dataset captures the distinct .NET and Windows-centric development ecosystem that flourished before the industry standardizing on GitHub.

Key Stats:

- 5,043,730 files from 38,087 repositories
- 3.6 GB compressed Parquet
- 91 programming languages (Heavily featuring C#, ASP.NET, and C++)
- Cleaned of binaries, build artifacts, and vendor directories (node_modules, packages)
- Includes platform-specific license metadata (Ms-PL, Ms-RL)

reacted to raincandy-u's post with 😎 24 days ago

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Introducing Rain-v2: Democratizing LLM training on gaming GPUs! ⚡

Following Rain-100M, we’re scaling up. Rain-v2 features a larger training dataset.

We’ve published a comprehensive blog covering the end-to-end journey—from raw data collection to rigorous evaluation and safety testing.

HF Repo: 🤗 raincandy-u/Rain-v2

Blog: 📚
https://angelkawaii.xyz/2026/01/29/rain-v2/

Special thanks to the open-source community and the SmolLM2 team for their foundational work! 🚀

HuggingFaceTB
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model (2502.02737)

posted an update 29 days ago

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🌐 NNTP Discussion Archives - 387M Messages from Public Newsgroups - nyuuzyou/nntp-text-387m

Here's something different from the code datasets: 20+ years of public discussion archives from NNTP newsgroups. Clean Parquet format, but this time it's conversations instead of code.

Key Stats:
- 386,629,949 messages from 159,345 newsgroups
- 191 GB compressed Parquet storage
- Spans 2002-2026
- Multilingual: English, German, French, Italian, Dutch, Polish, Russian, and others
- Email addresses redacted for privacy

The data is messy in the way real discussions are messy. Spam wasn't filtered out - you get the advertisements, the arguments, the off-topic threads, all of it. If you want sanitized text, this isn't it. If you want to see how people actually talked online before Discord and Reddit took over, here you go.

Processing kept it simple: convert everything to UTF-8, remove exact duplicates, strip binary attachments, redact emails. Legacy character encodings were a nightmare - had to handle Windows-1252, ISO-8859 variants, KOI8-R, Shift-JIS, GBK, and others just to get readable text. At least it was fun to do, and I think the result turned out pretty well. I hope someone else will also be able to have fun or gain something useful from this project.

reacted to raincandy-u's post with 🔥 about 1 month ago

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🤗 Just released Rain-100M, an experimental ~97M-parameter Qwen3-style language model trained from random initialization.

Repo: raincandy-u/Rain-100M

Data: HuggingFaceFW/fineweb-edu, ~3B tokens, English only

Tokenizer: custom 16k BPE, context length 4096

Architecture: 12 Transformer layers, hidden size 768, 12 heads, MLP 2048, SiLU, bf16

Rain-100M is a raw base model (not instruction-tuned or safety-aligned), aimed at small-scale research, debugging training pipelines, and CPU/edge experiments. If you run evaluations, finetunes, or visualizations with it, I would be very interested in your results!

3 replies

reacted to ZennyKenny's post with 🚀 about 1 month ago

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😎 My new personal website is live! Check out https://kennethhamilton.me to chat with an LLM about my professional skills and personal projects.

🙈 Think of it like a really, really vain version of ChatGPT.

6 replies

posted an update about 1 month ago

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🏛️ Google Code Archive Dataset - nyuuzyou/google-code-archive

Expanding beyond the modern code series, this release presents a massive historical snapshot from the Google Code Archive. This dataset captures the open-source landscape from 2006 to 2016, offering a unique time capsule of software development patterns during the era before GitHub's dominance.

Key Stats:

- 65,825,565 files from 488,618 repositories
- 47 GB compressed Parquet storage
- 454 programming languages (Heavily featuring Java, PHP, and C++)
- Extensive quality filtering (excluding vendor code and build artifacts)
- Rich historical metadata: original repo names, file paths, and era-specific licenses

This is one of those releases that I'm most interested in getting feedback on. Would you like to see more old code datasets?

reacted to ZennyKenny's post with 🔥 about 1 month ago

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🎉 Wow. Congratulations @bfirsh and the Replicate team on the CloudFlare acquisition!

✌️ You've really built an incredible ecosystem and product offering and should be super proud.

posted an update about 1 month ago

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🇨🇳 GitCode Dataset - Continuing the Chinese Code Series nyuuzyou/gitcode-code

Following up on the Gitee release, here's another major Chinese code dataset from GitCode (CSDN's code hosting platform). Same pipeline, same clean format, more valuable data from China's developer ecosystem.

Key Stats:
- 48,142,567 files from 85,632 repositories
- 40 GB compressed Parquet storage
- 537 programming languages
- Extensive quality filtering applied
- Rich metadata: repo names, file paths, licenses, and sizes

The final dataset in the Chinese code series is also available: nyuuzyou/jihulab-code. It's smaller in size but shares the same pipeline and formatting.

replied to Ujjwal-Tyagi's post about 1 month ago

Glad you are finding it useful! You should also check out these datasets:

https://huggingface.co/datasets/nyuuzyou/gitcode-code
https://huggingface.co/datasets/nyuuzyou/jihulab-code

They use the same data processing pipeline and format, but they are sourced from different Chinese services.

reacted to Ujjwal-Tyagi's post with 🤗 about 1 month ago

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I am very excited to see the release of nyuuzyou/gitee-code. This is exactly what I have been looking for. Thank you to @nyuuzyou for his hard work on this.

3 replies

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