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GAMMA

A toolkit for exploring, measuring, comparing, and improving language models through interactive and reproducible experiments.

What GAMMA Means

GAMMA is deliberately a family name rather than one rigid expansion. Each backronym names a real project surface or goal:

Context Reading What it names
Interactive game Game Analyzing Model Methods Attentively Predicting model continuations and inspecting the choices behind them.
Comparison and benchmarking Guessing Alternative Model Mechanics Analytically Comparing models, engines, decoding policies, and performance under recorded contracts.
Learning and interpretability Grasping Attention Mechanism Mysteries Accessibly Making logits, tokenization, attention-capable backends, and generation mechanics understandable.
SAME-R research Generalized Approach Matching, Measurement, and Attribution Testing different methods under matched evaluation and determining what caused an observed improvement.

These are contextual readings, not separate product names. GAMMA remains the stable project and command identity.

Choose a Surface

Surface Purpose Starting point
Game and chat Explore next-token prediction interactively. python gamma.py game
Comparison and benchmarking Compare model behavior, throughput, latency, and code generation. python gamma.py comparison or python gamma.py benchmark
Mind Meld Coordinate and swap among multiple model engines. python gamma.py mind-meld
SAME-R Compare prompts, data, teachers, training methods, routers, kernels, or other approaches under matched rims. projects/samer/README.md
Domain research Run translation, embedding, WGSL, compression, and other owned experiments. projects/
Integrations Connect Gamma through APIs, MCP, and supported model engines. docs/integration-guide.md

Quick Start

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python gamma.py game

Engine-specific setup is in src/engines/README.md.

SAME-R Research Method

SAME-R is Gamma's implementation-neutral outer method: Swappable Approaches under Matched Evaluation and Replication. Its recursive expansion is SAMER Applies Methods, Evaluates, Repeats.

Different inners. Same rims.

The inner approach can be human or agent labeling, data construction, prompt search, SFT, distillation, preference or policy optimization, routing, kernel search, or a future method. SAME-R keeps the objective, evaluator, controls, replication policy, receipts, and promotion boundary matched. A SAME-R instance may itself run as an inner approach.

Gamma currently executes SAME-R through domain project scripts, manifests, and human-selected interventions. The shared automatic approach registry and selector remain an explicit implementation boundary.

Repository Layout

The root is limited to stable entrypoints, project metadata, and tool configuration.

Path Ownership
src/ Gamma runtime, engines, game, benchmarks, and integrations
projects/ Self-contained research and distillation work
tools/ Operator-facing utilities and model analysis
requirements/ Engine and hardware-specific dependency manifests
docs/ Canonical architecture and usage documentation
tests/ Automated test suites

Keep generated reports under reports/, run output under its owning project, and new project-specific utilities beside that project rather than at repository root.

CLI Surface

python gamma.py [command]
Command Purpose
game Interactive gameplay and chat-style runs
comparison Side-by-side model comparison
mind-meld Multi-model collaboration and swapping
benchmark Throughput/latency benchmarking
codegen Code-generation benchmark workflows
list List available models
select Interactive model/engine selector
help Command help
python gamma.py help
python gamma.py help benchmark
python gamma.py help codegen
python gamma.py game --comparison --help
python gamma.py mind-meld --help

Canonical Documentation

Integrations and Ecosystem

License

MIT. See LICENSE.

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Low-level local LLM experiments, tools, and games

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