t.d.a.g. PRO

sequelbox

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AI & ML interests

open source, infinite games. (they/them)

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liked a model 1 day ago

yuxinlu1/gemma-4-12B-agentic-fable5-composer2.5-v2-3.5x-tau2

repliedto their post 1 day ago

published a model 1 day ago

sequelbox/Qwen3.6-27B-Esper4ThinkingCap

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replied to their post 1 day ago

added some Esper 4 merges for Qwen 3.6 and Gemma 4:

https://huggingface.co/sequelbox/Qwen3.6-27B-Esper4Carnice
https://huggingface.co/sequelbox/Qwen3.6-27B-Esper4Grug
https://huggingface.co/sequelbox/Qwen3.6-27B-Esper4Musa
https://huggingface.co/sequelbox/Qwen3.6-27B-Esper4Tachibana
https://huggingface.co/sequelbox/Qwen3.6-27B-Esper4Tess
https://huggingface.co/sequelbox/Qwen3.6-27B-Esper4ThinkingCap

https://huggingface.co/sequelbox/gemma-4-12B-it-Esper4FableComposer
https://huggingface.co/sequelbox/gemma-4-12B-it-Esper4Grug
https://huggingface.co/sequelbox/gemma-4-12B-it-Esper4Tachibana

replied to their post 19 days ago

GGUFs for Esper 4 and Guardpoint:

https://huggingface.co/mradermacher/gemma-4-12B-it-Esper4-i1-GGUF
https://huggingface.co/mradermacher/gemma-4-12B-it-Esper4-GGUF
https://huggingface.co/mradermacher/gemma-4-12B-it-Guardpoint-i1-GGUF
https://huggingface.co/mradermacher/gemma-4-12B-it-Guardpoint-GGUF

replied to their post 20 days ago

Esper 4 is now available for Gemma 4 12B: https://huggingface.co/ValiantLabs/gemma-4-12B-it-Esper4

posted an update 20 days ago

Post

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Multiple NEW RELEASES for Gemma 4 12B!

- Esper 4, our flagship agentic coder: specialist in coding, architecture, DevOps, and MLOps!
- Tachibana-Agent, trained only on code for dedicated, predictable deployment!
- Guardpoint, our structured medical reasoning model: medical diagnosis, management, knowledge, and understanding in structured, concise form!

GET OUR NEW MODELS:

ValiantLabs/gemma-4-12B-it-Esper4
sequelbox/gemma-4-12B-it-Tachibana-Agent
ValiantLabs/gemma-4-12B-it-Guardpoint

Get the datasets for your own training:
sequelbox/Titanium4-DeepSeek-V4-Pro
sequelbox/Mitakihara2-DeepSeek-V4-Pro
sequelbox/Tachibana4-DeepSeek-V4-Pro
sequelbox/Superpotion-DeepSeek-V3.2-Speciale

Esper 4 is also available for Qwen 3.6 27B: ValiantLabs/Qwen3.6-27B-Esper4

We'll be expanding Esper 4 to more models and releasing new models as funding allows - donate for more, faster, better models and datasets: sequelbox/SupportOpenSource

More to come soon!

go build stuff :)
allegra

2 replies

reacted to Quazim0t0's post with ❤️🔥 24 days ago

Post

2916

🧩 Verified neural units, now for memory & storage

Following up on my neural-aarch64-units (small MLPs that emulate CPU datapath slices, verified bit-exact over their entire finite input domain — N/N), I applied the same discipline to memory and storage. Three new repos:

🔷 neural-ddr — verified units emulating DDR5 logic: DBI (256/256, 512/512), ADDR_MAP (4096/4096), CMD_DECODE (32/32), WR_CRC (512/512), and on-die ECC ODECC (256/256, 3328/3328). Composed into a bridge that presents DDR5 behavior over real DDR3/DDR4 RAM — flip a bit in every stored byte, ECC corrects all of them.
🤗 Quazim0t0/neural-ddr · 💻 https://github.com/quzi93/neural-ddr

🗄️ neural-storage — a self-healing vault on a neural-verified GF(2⁸) core (LOG/EXP compose to a multiply verified over all 65,536 pairs). Content-addressed dedup + Reed-Solomon so any k of n shards rebuild the whole, plus a whole-drive → self-healing .pt imager.
🤗 Quazim0t0/neural-storage · 💻 https://github.com/quzi93/neural-storage

💿 neural-cd-preserve — scan a disc into a self-healing .pt that detects (per-shard SHA-256) and repairs bit-rot, restoring bit-exact even from a damaged copy. Beyond the RS limit it's flagged LOST, never silently wrong.
🤗 Quazim0t0/neural-cd-preserve · 💻 https://github.com/quzi93/neural-cd-preserve

Build your own: golden finite function → enumerate the domain (decompose big/linear ops like CRC/ECC/GF into bit/byte slices) → train a small MLP → verify must be bit-exact on 100% of inputs or it's rejected → compose. Every repo ships the training + exhaustive-verification scripts.

Honest by construction: dedup removes redundancy, erasure coding adds it, ECC corrects faults — none of it pretends to beat entropy. Runs on modest/older hardware. 🤗

1 reply

replied to their post about 1 month ago

GGUFs are now available:

https://huggingface.co/mradermacher/Qwen3.6-27B-Esper4-i1-GGUF
https://huggingface.co/mradermacher/Qwen3.6-27B-Esper4-GGUF

more to come very soon!

replied to their post about 1 month ago

thank you! the Esper 4 mix is interesting because the datasets obviously have a lot of fundamental overlap; there are plenty of code tasks in Titanium/Mitakihara that could reasonably be in the Tachibana dataset, and some in Tachibana that could have gone the other way. by including the ~25% mix of 'old' queries in Titanium and Mitakihara it provides some balance here (many of the old Mitakihara queries in particular are chat/knowledge queries 'about' AI and AI-adjacent topics instead of specific tasks for the AI to perform) while still being highly relevant to Esper users.

have fun building :)

posted an update about 1 month ago

Post

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NEW RELEASE: Esper 4 is here for Qwen 3.6 27b, along with our new datasets!

- NEW DATASET: Titanium 4 maximizes DevOps and architecture helpfulness, powered by high-difficulty agentic-focused DevOps and architecture data generated with DeepSeek-V4-Pro!
- NEW DATASET: Mitakihara 2 brings AI coding and expertise data for AI development, research, deployment, interpretability, operation and experimentation!
- Improved coding performance: challenging agentic coding queries from Tachibana 4 allow Esper 4 to tackle harder coding tasks across a variety of languages!

GET ESPER 4: ValiantLabs/Qwen3.6-27B-Esper4

Get the datasets for your own training:
sequelbox/Titanium4-DeepSeek-V4-Pro
sequelbox/Mitakihara2-DeepSeek-V4-Pro
sequelbox/Tachibana4-DeepSeek-V4-Pro

We've been working hard on Esper 4 - it's so exciting to finally bring it to everyone! We hope it helps you build.

We'll be expanding Esper 4 to more models as funding allows - donate for more, faster, better models and datasets: sequelbox/SupportOpenSource

The revolution is coming - we're here to fight for AI you can use and build on your own computer, not a giant corporation charging you for access at their discretion. We've seen what OpenAI, Anthropic, and the ultra-rich taking charge of the AI future looks like, and it's already very clear you won't like living in it. Choose a different future while you still can.

Open source must win.

More to come soon!

love, always,
allegra

4 replies

reacted to danielhanchen's post with 🚀 3 months ago

Post

6004

We’re excited to announce that Unsloth has joined the PyTorch Ecosystem! 🔥🦥

Unsloth is an open-source project that makes training & running models more accurate and faster with less compute. Our mission is to make local AI accessible to everyone. Thanks to all of you for making this possible! 💕

Blog: https://unsloth.ai/blog/pytorch
GitHub: https://github.com/unslothai/unsloth

2 replies

reacted to unmodeled-tyler's post with ❤️ 3 months ago

Post

4131

Hey Hugging Face!

Repo: https://github.com/unmodeled-tyler/vessel-browser

I wanted to share a cool feature from my open source AI native web browser, Vessel: Persistent highlights!

You can highlight anything on the page and the context is provided to the agent. It's kind of a fun way to learn about new stuff, synthesize info, or just deepen your comprehension/understanding.

Since highlights are persistent, you can close the page, come back later - and your highlights will be exactly where you left them. I've found this particularly useful when reviewing technical blogs, model cards, etc.

Check it out!

1 reply

posted an update 3 months ago

Post

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JUST RELEASED: the Tachibana 4 DeepSeek-V4-Pro dataset and our all-new Tachibana-Agent coding model!

- Questions prioritize real-world, challenging agentic coding tasks across a variety of programming languages and topics. Synthetic prompts utilize a variety of personas, experience levels, and styles of communication to maximize real-world flexibility and usability.
- Areas of focus include back-end and front-end development, systems programming, distributed systems, performance optimization, data structures, databases and data engineering, game and mobile development, security engineering, compiler design, custom tooling, task automation, practical bugfixes, and more!
- A wide variety of emphasized languages improves development capability: Python, C, C++, C#, Go, TypeScript, Java, JavaScript, Rust, Haskell, SQL, Shell, R, Ruby, assembly code, and more!

The new dataset: sequelbox/Tachibana4-DeepSeek-V4-Pro
The new model: sequelbox/Qwen3.6-27B-Tachibana-Agent

We're thrilled to bring this to everyone - try it out and see what you think!

Tachibana 4 is the first of several datasets used for the upcoming Esper 4! See what we're working on and help our releases come out faster: sequelbox/SupportOpenSource

Open source will win :)

love,
allegra

posted an update 3 months ago

Post

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EARLY SNEAK PREVIEW of our first DeepSeek-V4-Pro dataset, Tachibana 4!

Tachibana 4 is our upcoming agentic coding dataset:
- Questions prioritize real-world, challenging agentic coding tasks across a variety of programming languages and topics.
- Areas of focus include back-end and front-end development, systems programming, distributed systems, performance optimization, data structures, databases and data engineering, game and mobile development, security engineering, compiler design, custom tooling, task automation, practical bugfixes, and more!
- A wide variety of emphasized languages improves development capability: Python, C, C++, C#, Go, TypeScript, Java, JavaScript, Rust, Haskell, SQL, Shell, R, Ruby, assembly code, and more!
- Synthethic prompts utilize a variety of personas, experience levels, and styles of communication to maximize real-world flexibility and usability.

Get it now: sequelbox/Tachibana4-DeepSeek-V4-Pro-PREVIEW

These agentic datasets will power the upcoming Esper 4, and whatever you can build! We'll have more finetunes on the way as well! :) we're going to make open source better and better for your work!

If you would like to see Esper 4 and these datasets faster, this is the best way you can help us: sequelbox/SupportOpenSource

for freedom, with love,
allegra

replied to their post 3 months ago

Qwen 3.6 27B available as well: https://huggingface.co/ValiantLabs/Qwen3.6-27B-Esper3.1

Quants for both are up too:
https://huggingface.co/mradermacher/Qwen3.6-35B-A3B-Esper3.1-i1-GGUF
https://huggingface.co/mradermacher/Qwen3.6-35B-A3B-Esper3.1-GGUF
https://huggingface.co/mradermacher/Qwen3.6-27B-Esper3.1-i1-GGUF
https://huggingface.co/mradermacher/Qwen3.6-27B-Esper3.1-GGUF

posted an update 4 months ago

Post

1929

NEW RELEASE: Esper 3.1 for Qwen 3.6!

- Your dedicated DevOps expert: Esper 3.1 maximizes DevOps and architecture helpfulness, powered by high-difficulty DevOps and architecture data generated with DeepSeek-V3.1-Terminus!
- Improved coding performance: challenging code-reasoning datasets stretch DeepSeek-V3.1-Terminus and DeepSeek-V3.2 to the limits, allowing Esper 3.1 to tackle harder coding tasks!
- AI to build AI: our high-difficulty AI expertise data boosts Esper 3.1's MLOps, AI architecture, AI research, and general reasoning skills.

Get it now: ValiantLabs/Qwen3.6-35B-A3B-Esper3.1

We're working on more finetunes for the newest Qwen and Gemma models, and we've also started working on the agentic-first datasets for Esper 4 :) we're going to make open source better and better for your work!

Please note that real life financial and family concerns have popped up and have imposed unfortunate limitations on our ability to devote time to our open-source work :( If you would like to see Esper 4 and our other releases speed up instead of slowing down, this is the best way you can help us: sequelbox/SupportOpenSource

No matter what, we'll keep fighting and we won't give up!

with love,
allegra

1 reply

posted an update 4 months ago

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Multiple new releases for Gemma 4!

For Gemma 4 31B: Guardpoint, our medical reasoning model, trained on medical knowledge, management, diagnosis, and tasks:
- Structured medical reasoning responses are efficient and informative, cutting token costs for faster inference!
- Wide-ranging knowledge base: trained on a wide variety of medical disciplines, patient types, and query structures!
- High quality medical responses emphasize performance, brevity, specificity, statistical rationality, and openness.

Get Guardpoint for Gemma 4: ValiantLabs/gemma-4-31B-it-Guardpoint

For Gemma 4 E4B and E2B: Shining Valiant 3, our science-reasoning model!
- Science-reasoning: physics, biology, chemistry, compsci, astronomy, Earth science, and information theory.
- AI to build AI: high-quality reasoning performance on AI, MLOps, math and CUDA, complex adaptive and agentic systems, cognition, logic, linguistics, simulation, knowledge management, and more!
- Supplemented creative reasoning and general chat performance.

Get the new SV3 models:
E4B: ValiantLabs/gemma-4-E4B-it-ShiningValiant3
E2B: ValiantLabs/gemma-4-E2B-it-ShiningValiant3

We're working on several things - most excitingly, we've officially started the dataset curation process for Esper 4! We're focused on enhanced agentic capability and higher-dififculty, higher-value tasks this time, very excited to bring this to everyone when we can :)

Help support our releases, donations used for our experimental models and datasets: sequelbox/SupportOpenSource

Fight for open source with us!

for love and friendship,
allegra

reacted to mayafree's post with 🔥 5 months ago

Post

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Leaderboard of Leaderboards — A Real-Time Meta-Ranking of AI Benchmarks

MAYA-AI/all-leaderboard

Hundreds of AI leaderboards exist on HuggingFace. Knowing which ones the community actually trusts has never been easy — until now.

Leaderboard of Leaderboards (LoL) ranks the leaderboards themselves, using live HuggingFace trending scores and cumulative likes as the signal. No editorial curation. No manual selection. Just what the global AI research community is actually visiting and endorsing, surfaced in real time.

Sort by trending to see what is capturing attention right now, or by likes to see what has built lasting credibility over time. Nine domain filters let you zero in on what matters most to your work, and every entry shows both its rank within this collection and its real-time global rank across all HuggingFace Spaces.

The collection spans well-established standards like Open LLM Leaderboard, Chatbot Arena, MTEB, and BigCodeBench alongside frameworks worth watching. FINAL Bench targets AGI-level evaluation across 100 tasks in 15 domains and recently reached the global top 5 in HuggingFace dataset rankings. Smol AI WorldCup runs tournament-format competitions for sub-8B models scored via FINAL Bench criteria. ALL Bench aggregates results across frameworks into a unified ranking that resists the overfitting risks of any single standard.

The deeper purpose is not convenience. It is transparency. How we measure AI matters as much as the AI we measure.

5 replies

posted an update 5 months ago

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Multiple new releases for Qwen 3.5 27B!

Firstly, Guardpoint, our medical reasoning model; trained on medical knowledge, management, diagnosis, and tasks:
- Structured medical reasoning responses are efficient and informative, cutting token costs for faster inference!
- Wide-ranging knowledge base: trained on a wide variety of medical disciplines, patient types, and query structures!
- High quality medical responses emphasize performance, brevity, specificity, statistical rationality, and openness.

Get Guardpoint for Qwen 3.5 27B: ValiantLabs/Qwen3.5-27B-Guardpoint

Secondly, we've also brought DAG Reasoning to Qwen 3.5 27B:
- Create structured, analytical Directed Acyclic Graphs to provide insight into your queries and situations!
- Multi-step analysis identifies causal relationships, produces confidence measurements, and forms a single structured graph object.
- DAG Reasoning Format provides clear, readable JSON containing structured, useful information; easy to use for creating visualizations, doing analysis, or further conversation with your assistant.
- Trained in a variety of subjects for flexible analysis: programming, science, business, economics, finance, law, logistics, management, and more!

Get the newest DAG Reasoning release: sequelbox/Qwen3.5-27B-DAG-Reasoning

We also have Esper 3.1 available for Qwen 3.5 27B - focused on high-performance coding, DevOps, and architecture: ValiantLabs/Qwen3.5-27B-Esper3.1

We'll have a lot more to come for the high-performance Qwen 3.5! Most of it is waiting for Deepseek V4 to come out first :) We've got some fun ideas!

Help support our releases, donations used for our experimental models and datasets: sequelbox/SupportOpenSource

Fight for open source with us! We've got a lot to do.

for friendship,
allegra

replied to their post 5 months ago

a silver lining: as this issue has nothing to do with training, only merging, there shouldn't be any delays to our other planned Qwen 3.5 releases this week. We'll work hard to get those out for everyone's use.

posted an update 5 months ago

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IMPORTANT corrective note/apology: the initial upload of ValiantLabs/Qwen3.5-27B-Esper3.1 contained improperly merged weights, meaning it was effectively just Qwen 3.5. We've merged properly now and re-uploaded the correct weights to the existing repository.

The model link is here: ValiantLabs/Qwen3.5-27B-Esper3.1

This is not at all the fault of Qwen 3.5, transformers, or anything other than our own flawed upload pipeline and insufficient post-upload validation. We have to do better. We'll immediately improve our validation procedures to be more rigorous. This will never happen again.

We are proud to build quickly: by providing a quick finetune of a new high-performance model like Qwen 3.5, we seek to provide value not only in the model's direct use but especially to our fellow open-source creators, who can learn from our initial training attempt. We are proud that building fast helps you build fast. In this case, our poor work has produced the opposite result - we've wasted your time. We are really sorry to everyone, but especially our fellow builders.

We feel about one inch tall right now, but we're going to get back to work and do better. Our crew deserves better and so do our users.

Humbly, your captain,
t.d.a.g.

1 reply

t.d.a.g. PRO

AI & ML interests

Recent Activity

Organizations

sequelbox's activity