🤝 Open to Collab

Eric PRO

Dorman11

AI & ML interests

Currently training Endeavor, a SLM model! Interests include: Agentic security, Machine Learning, Reinforcement Learning, PyTorch and all around web dev ninja! Level II Specialist working in Cyber Security field.

Recent Activity

updated a Space about 12 hours ago

Dorman11/open-mythos-run

updated a bucket about 13 hours ago

Dorman11/datasetdb

reacted to maglun's post with 🚀 1 day ago

I work on quantizing models to run efficiently on local hardware, and kept being curious how existing quants spend their "bit budget" during optimization and built a local tool to explore. Many quants apply one setting across all tensors, but some do more interesting things: the model in the screenshot holds attention K at 4.5 bits while Q/V/O get 8.5, and protects layer 0 MLP. It turned out useful enough that I made it public: https://tensorlens.dev Explore any HF model in the browser without downloading it. The anatomy map is read from the safetensors header via a range request, and only tensors you click ever stream. Large tensors are sampled rather than streamed in full. Limitations: safetensors only (no GGUF yet), some exotic variants don't work yet, and gated repos aren't supported yet. Feedback very welcome, especially models that break it.

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Organizations

updated a Space about 12 hours ago

Open Mythos Run

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Train and test a tiny character‑level language model on your text

updated a bucket about 13 hours ago

Dorman11/datasetdb

439 MB

reacted to maglun's post with 🚀 1 day ago

Post

1146

I work on quantizing models to run efficiently on local hardware, and kept being curious how existing quants spend their "bit budget" during optimization and built a local tool to explore. Many quants apply one setting across all tensors, but some do more interesting things: the model in the screenshot holds attention K at 4.5 bits while Q/V/O get 8.5, and protects layer 0 MLP.

It turned out useful enough that I made it public: https://tensorlens.dev

Explore any HF model in the browser without downloading it. The anatomy map is read from the safetensors header via a range request, and only tensors you click ever stream. Large tensors are sampled rather than streamed in full.

Limitations: safetensors only (no GGUF yet), some exotic variants don't work yet, and gated repos aren't supported yet.

Feedback very welcome, especially models that break it.

5 replies

replied to maglun's post 1 day ago

This a great to use! I checked Kimi-K3 with it. Very nice man!

liked a model 1 day ago

moonshotai/Kimi-K3

Image-Text-to-Text • 2.8T • Updated 15 days ago • 1.57M • • 10.5k

reacted to KlondikeDev's post with 🔥 1 day ago

Post

2081

Boris-2 coming soon!

The Models:

Boris-2-75M: Trained on 26B tokens -- estimated to start training on August 12th.
Boris-2-125M: Trained on 90B tokens -- Estimated to start training on August 20th.
Boris-2-250M: Trained on 60B tokens -- Estimated to start training on September 10th.

Why does 125M get more tokens than 250M?

Well, the straight answer is time. It saves time, while still allowing the 250M model to exceed the 125M model.

Furthermore, we are attempting a unique architecture and layering scheme to hopefully end up around the strength of SmolLM2-135M. Fingers crossed!

We hope to end up in the ballpark of AxiomicLabs/GPT-X2.5-135M or BananaMind/BananaMind-2-Pro-Preview

Following this, we will release the Pro, Instruct and Pro-Instruct variants. More info will be coming soon!

4 replies

reacted to dddyym's post with 🔥 1 day ago

Post

1905

Released mlquantx 0.2.6: a reproducible PyTorch workflow for cross-sectional multi-factor research.

pip install --upgrade mlquantx
mlquant demo

The demo runs synthetic data → 213 factors → MLP → portfolio construction → cost-aware backtest. CI covers Python 3.9–3.11 with 96 tests.

Dataset: dddyym/ml-quant-trading-synthetic
Checkpoint: dddyym/ml-quant-trading-synthetic-mlp
GitHub: https://github.com/initial-d/ml-quant-trading
PyPI: https://pypi.org/project/mlquantx/

Research and teaching use only — not a live-trading system or a profitability claim.

published a Space 1 day ago

Open Mythos Run

⚡

Train and test a tiny character‑level language model on your text

posted an update 1 day ago

Post

I've been thinking this for a long time, other than OpenMythos will we see similar type of open source models be released? The more and more top frontier models get good at finding zero day vulnerabilities and security weaknesses how will the open source model community respond. My take is we will see a open source model very soon be as good at finding security holes as the top models, at some point in the future. Is it just me or anyone seeing this?

updated a Space 1 day ago

Aurora Lm Train

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published a Space 1 day ago

Aurora Lm Train

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replied to Banaxi-Tech's post 2 days ago

BananaOS I assume could run other small models aside from BananaMind models? I’m training a small model and was just curious…either way this is a really cool idea!