Metadata-Version: 2.4
Name: brsx
Version: 0.3.0
Summary: AutoForge — automatic model building, training, and fine-tuning that calibrates to your hardware
Author-email: Baris Ciftci <brscftc0@gmail.com>
License-Expression: Apache-2.0
Keywords: machine-learning,transformer,training,fine-tuning,mtp,autoforge
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch>=2.0
Requires-Dist: huggingface_hub
Requires-Dist: tokenizers
Requires-Dist: transformers
Requires-Dist: peft
Requires-Dist: accelerate
Requires-Dist: psutil
Provides-Extra: qlora
Requires-Dist: bitsandbytes; extra == "qlora"
Dynamic: license-file

# brsx

**AutoForge** — build, train, and fine-tune models that calibrate themselves to your hardware.

brsx probes your GPU/CPU by actually running a few steps, picks a model size that
fits your memory and speed target, and trains it. No config wrestling — pick a mode
and go.

## Install

```bash
pip install brsx
```

Optional extras (installed only if you need them):

```bash
pip install brsx[finetune]   # HuggingFace fine-tuning (transformers, peft, accelerate)
pip install brsx[qlora]      # 4-bit QLoRA (bitsandbytes, Linux/CUDA)
pip install brsx[tokenizer]  # fast BPE for the MTP branch
pip install brsx[all]        # everything
```

## Usage

```python
from brsx import automodel

automodel.run()
```

You'll get a menu:

```
1) Transformer training        — train a standard Transformer from scratch
2) MTP Transformer training    — Multi-Token Prediction heads (DeepSeek-V3 style)
3) HuggingFace model fine-tune — fine-tune a HF model (local path or hub id)
4) brsx (.pt) model fine-tune  — fine-tune an existing brsx model
```

Pick one and follow the prompts — everything (mode, learning rate, steps,
checkpointing, data source) is asked interactively.

## License

Apache-2.0. See [LICENSE](LICENSE).
