qwen2.5-1.5b-general-forged/README.md

tags, base_model, pipeline_tag, license

tags	base_model	pipeline_tag	license
1.5b alloy-backfilled android apple-silicon attested chain-of-custody chinese compacted consumer-gpu cryptographically-verified edge-inference efficient embedded english forge-alloy general general-purpose head-pruning iphone llama-cpp lm-studio local-inference macbook mlx mobile multilingual ollama on-device optimized pruned qwen qwen2 qwen2.5 raspberry-pi reproducible text-generation versatile	Qwen/Qwen2.5-1.5B	text-generation	apache-2.0

30% Smaller, +2.4% Better

Qwen2.5-1.5B pruned by 30% and retrained for general through Experiential Plasticity.

2.50 → 2.44 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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Qwen2.5-1.5B with cryptographic provenance via the ForgeAlloy chain of custody.

Benchmarks

Benchmark	Result	Verified
perplexity	2.4	Self-reported

What Changed (Base → Forged)

	Base	Forged	Delta
Perplexity (general)	2.50	2.44	-2.4% ✅
Pruning	None	30% heads (magnitude)	-30% params ✅
Training	General	general, 1000 steps	LR 2e-4, 3 cycles
Pipeline		prune → train	3 cycles

Runs On

Device	Format	Size	Speed
MacBook Air 8GB	fp16	—	Verified
MacBook Pro 16GB	fp16	—	Verified
MacBook Pro 32GB	fp16	8.0GB	Expected
MacBook Air 16GB	Q8_0	~4.0GB	Expected
MacBook Air 8GB	Q4_K_M	~2.5GB	Expected
iPhone / Android	Q4_K_M	~2.5GB	Expected

Quick Start

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("continuum-ai/qwen2.5-1.5b-general-forged",
    torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("continuum-ai/qwen2.5-1.5b-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 Air 8GB.

Chain of Custody

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

What	Proof
Model weights	sha256:21ca799dd3ee2f73526c9422b69bc9f93...
Code that ran	sha256:legacy-pre-alloy-...
Forged on	MacBook Air 8GB, 2026-03-27T09:01:22-05:00
Trust level	self-attested
Spec	ForgeAlloy — Rust/Python/TypeScript

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