A / THE MODEL
Start at
the weights.
ABLE-Origin explores training a language model from scratch: architecture, tokenizer, training, and the evidence left by a run.
Read the model record ↗ABL—000 / THE WORK, MADE VISIBLE
An independent AI lab exploring local models, agents, persistent memory, and the engineering between an idea and something you can inspect.
Enter the laboratory ↓A / THE MODEL
ABLE-Origin explores training a language model from scratch: architecture, tokenizer, training, and the evidence left by a run.
Read the model record ↗B / THE SYSTEM
Local inference, agent routes, memory and application data controls form different engineering problems. A system diagram should make their boundaries easier to understand.
Inspect the public source excerpt ↗C / THE EVIDENCE
Measurements become useful when the configuration, source and limits stay attached. Follow the evidence into a real experiment below.
Inspect an inference result ↓D / THE PUBLIC EDGE
This proposal separates public project evidence from owner decisions and private runtime data. The journal below contains no fabricated updates.
Approach the journal ↓§02 / SELECTED RESEARCH RECORDS
Inspectable work, its source, and the limits that travel with it.
A language model, starting from initial weights.
29.9 million parameters. Custom architecture and tokenizer work. Trained on a consumer GPU with TinyStories.
Inspect source ↗FIG. 01 / SIX REPORTED VALIDATION CHECKPOINTS
Best reported: 1.341 at 60,000 steps
August 2026 source report. Dashed joins guide the eye. Raw logs and independent reproduction are not bundled here.
Article and context ↗| Training step | Loss | Note |
|---|---|---|
| 500 | 2.379 | Reported |
| 1,000 | 1.964 | Reported |
| 1,500 | 1.837 | Reported |
| 42,000 | 1.374 | Reported |
| 60,000 | 1.341 | Best reported |
| 61,894 | 1.344 | Final reported |
A constraint becomes the experiment.
Quantization, offloading and decoding under a tight GPU memory budget. Different configurations, visible tradeoffs.
Read the experiment ↗No throughput measurement. A failure is not a zero.
RTX 3070 Ti 8 GB · i7-12700K · WSL2. Source-reported outcomes, not rerun for this atlas. Prompt counts, repetitions and timing details are incomplete; comparisons are illustrative.
Inspect source and limitations ↗Explorations in local model routes, persistent memory and application-level data controls.
Read about ABL Core ↗EXPLANATORY SCHEMATIC / NOT LIVE TOPOLOGY
§03 / THE INSTRUMENT
A spectral index of the work. Select a layer to inspect its role.
01 / MODEL
Architecture, tokenizer and training work in ABLE-Origin.
Read the model experiment ↗02 / SERVING
Quantization, GPU offload and decoding experiments under hardware constraints.
Read the local inference article ↗03 / SYSTEM
Public source excerpts explore agent routes, memory and application data controls.
Inspect ABL Core ↗04 / RECORD
Source, timing, failures, limitations and review belong beside the conclusion.
Read the latest lab notes →§04 / THE PUBLIC JOURNAL
Real work. Inspectable evidence. A considered public record.
A development log should carry its source, work date, review and limitations. Read the November 4 and 5 candidate results: owned process cleanup, Promise rejection regressions and service-identity fences.
Open the journal →OWNER DECISIONS AND PRIVATE RUNTIME DATA STAY OUTSIDE THIS PUBLIC DESIGN.ABSENT BORN LABS / Asif
An interactive atlas of the lab’s engineering work. Public writing and source links open the current published work. The drawings describe architecture. Dated lab notes carry the measured results.