Metadata-Version: 2.1
Name: quarterbit
Version: 50.2.0
Summary: QuarterBit - Train AI models and earn $AXM on the AXIOM network. The first verifiable distributed AI training.
Home-page: https://quarterbit.dev
Author: Clouthier Simulation Labs
Author-email: Clouthier Simulation Labs <info@quarterbit.dev>
License: MIT
Project-URL: Homepage, https://quarterbit.dev
Project-URL: Documentation, https://quarterbit.dev/docs
Keywords: ai,training,distributed,axiom,blockchain,llm,memory-efficient
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.12
Description-Content-Type: text/markdown
Requires-Dist: numpy >=1.24.0
Requires-Dist: requests >=2.28.0
Provides-Extra: cli
Requires-Dist: typer >=0.9 ; extra == 'cli'
Requires-Dist: rich >=13.0 ; extra == 'cli'
Provides-Extra: full
Requires-Dist: torch >=2.0.0 ; extra == 'full'
Requires-Dist: cupy-cuda12x ; extra == 'full'
Requires-Dist: typer >=0.9 ; extra == 'full'
Requires-Dist: rich >=13.0 ; extra == 'full'
Provides-Extra: gpu
Requires-Dist: torch >=2.0.0 ; extra == 'gpu'
Requires-Dist: cupy-cuda12x ; extra == 'gpu'

# QuarterBit — Distributed AI Training on AXIOM

**The world's first mathematically verifiable distributed AI training network.**

---

## For Trainers — Earn $AXM With Your Hardware

### Why Train Now?

AXIOM is in **launch phase**. Early trainers have a unique opportunity:

- **Early $AXM acquisition** — Earn tokens before exchange listings
- **Growing network** — Less competition, more tasks per trainer
- **Multiplier bonuses** — Consistent trainers earn up to 10x rewards
- **First-mover advantage** — Build reputation and multipliers now

### Any Hardware Works

With Pipeline Parallelism, you only load **your assigned layers**, not the full model:

| Model | Full Size | Your Share (8 trainers) | Min GPU |
|-------|-----------|-------------------------|---------|
| GPT-2 | 2 GB | 250 MB | Any |
| LLaMA-7B | 14 GB | 1.7 GB | 4 GB |
| LLaMA-70B | 140 GB | 17 GB | 24 GB |
| 405B+ | 800+ GB | 100 GB | 2x A100 |

**Even a laptop GPU can train 70B models and earn $AXM.**

### Get Started in 3 Commands

```bash
pip install quarterbit[full]

quarterbit init        # Create wallet
quarterbit register    # Auto-detect hardware
quarterbit start       # Start earning
```

### Daemon Mode — Set and Forget

```bash
quarterbit daemon start    # Runs 24/7, auto-restarts
quarterbit stats --watch   # Watch earnings live
```

The daemon:
- Auto-selects highest-paying tasks for your hardware
- Restarts on crashes
- Claims rewards automatically
- Logs to `~/.quarterbit/logs/`

### Reward Multipliers

| Consistency | Multiplier | Earnings |
|-------------|------------|----------|
| New | 1.0x | Base rate |
| 50% | 1.3x | +30% |
| 80% | 1.8x | +80% |
| 95%+ | 2.5x+ | +150% |

**Reliable trainers earn significantly more per batch.**

---

## For AI Teams — Train Models Without Infrastructure

### Why Use AXIOM?

| Benefit | Details |
|---------|---------|
| **80%+ Cost Savings** | No GPU clusters, no cloud bills, pay only for compute used |
| **You Own Everything** | Your model, your data, your weights — we never store them |
| **Trustless Verification** | Mathematical proof of correct training, not trust |
| **Same Quality** | Identical results to centralized training |
| **No Infrastructure** | No DevOps, no cluster management, no maintenance |

### Security & Privacy

**Your data stays yours:**

- **End-to-end encryption** — Gradients encrypted with your keys (ECIES)
- **No data storage** — Training data never touches our servers
- **P2P architecture** — Trainers download from your source, not us
- **Auto-deletion** — Temporary data deleted within 1 hour

**Verification you can trust:**

- **VLA exact arithmetic** — Zero floating-point error accumulation
- **On-chain proofs** — Every gradient cryptographically verified
- **Stake slashing** — Cheating trainers lose their stake
- **Deterministic results** — Same output on any hardware

### How It Works

```
1. You submit a task with model + dataset + reward
2. Your data stays on YOUR servers (S3, IPFS, HuggingFace)
3. Trainers download only their assigned batches
4. Gradients encrypted and verified with VLA
5. You receive trained model — ownership never transfers
```

### Cost Comparison

| Approach | LLaMA-7B Training | LLaMA-70B Training |
|----------|-------------------|-------------------|
| AWS/GCP | $50,000+ | $500,000+ |
| Own cluster | $200,000+ hardware | $2M+ hardware |
| **AXIOM** | **Pay per batch** | **Pay per batch** |

### Quick Start

```python
from quarterbit import AxiomTaskSubmitter

submitter = AxiomTaskSubmitter(
    rpc_url="https://rpc.quarterbit.dev",
    private_key="0x..."
)

# Create task — your data stays on your servers
task = await submitter.create_task(
    model=my_model,
    dataset="s3://my-bucket/data",  # YOUR storage
    reward_per_batch=10,
    total_batches=1000
)

# Monitor training
async for progress in submitter.train_loop(task.task_id):
    print(f"Loss: {progress['loss']:.4f}")

# Get your trained model
trained_model = submitter.get_model()
```

---

## Installation

```bash
# Basic
pip install quarterbit

# With GPU + CLI (recommended)
pip install quarterbit[full]
```

## System Requirements

- **Python**: 3.12+
- **OS**: Windows, Linux, or WSL
- **GPU**: Optional (CUDA 12.x for acceleration)

## CLI Reference

```bash
# Wallet
quarterbit init              # Create wallet
quarterbit balance           # Check $AXM balance

# Training
quarterbit register          # Register hardware
quarterbit start             # Start training
quarterbit start --daemon    # Background daemon
quarterbit stop              # Stop gracefully

# Earnings
quarterbit stats             # Your statistics
quarterbit claim             # Claim rewards
quarterbit momentum          # View multiplier

# Daemon
quarterbit daemon start      # Start background
quarterbit daemon status     # Check status
quarterbit daemon logs       # View logs
```

## Links

- **Website**: https://quarterbit.dev
- **Documentation**: https://quarterbit.dev/docs

## License

MIT — Clouthier Simulation Labs 2026

Free to use. Decentralized architecture — anyone can run nodes.
