30% Smaller, +0.4% Better

Qwen2.5-3B pruned by 30% and retrained for general through Experiential Plasticity.

2.30 → 2.29 perplexity · 3 cycles

Every claim on this card is verified
Trust: self-attested · 1 benchmark · 2 devices tested
ForgeAlloy chain of custody · Download alloy · Merkle-chained

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Qwen2.5-3B with cryptographic provenance via the ForgeAlloy chain of custody.

Benchmarks

What Changed (Base → Forged)

Runs On

Quick Start

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("continuum-ai/qwen2.5-3b-general-forged",
    torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("continuum-ai/qwen2.5-3b-general-forged")

inputs = tokenizer("def merge_sort(arr):", return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(output[0], skip_special_tokens=True))

Methodology

Produced via head pruning. Full methodology, ablations, and per-stage rationale are in the methodology paper and the companion MODEL_METHODOLOGY.md in this repository. The pipeline ran as prune → train over 3 cycles on MacBook Pro 16GB.

Chain of Custody

Scan the QR or verify online. Download the alloy file to verify independently.

Make Your Own

Forged with Continuum — a distributed AI world that runs on your hardware.

The Factory configurator lets you design and forge custom models visually — context extension, pruning, LoRA, quantization, vision/audio modalities. Pick your target devices, the system figures out what fits.

GitHub · All Models · Forge-Alloy

License

apache-2.0