+22.7% Better at Code

Qwen3.5-4B forged for code through Experiential Plasticity.

3.04 → 2.35 perplexity · 3 cycles

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

Qwen3.5-4B with cryptographic provenance via the ForgeAlloy chain of custody.

Benchmarks

Benchmark	Result	Verified
perplexity	22.7	Self-reported
humaneval	pending	Self-reported

What Changed (Base → Forged)

	Base	Forged	Delta
Perplexity (code)	3.04	2.35	-22.7% ✅
Training	General	code, 1000 steps	LR 2e-4, 3 cycles
Pipeline		train → quant → eval → quant	3 cycles

Runs On

Device	Format	Size	Speed
NVIDIA GeForce RTX 5090	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/qwen3.5-4b-code-forged-GGUF",
    torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("continuum-ai/qwen3.5-4b-code-forged-GGUF")

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 GGUF quantization. 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 train → quant → eval → quant over 3 cycles on NVIDIA GeForce RTX 5090.

Chain of Custody

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

What	Proof
Model weights	`sha256:03dd512b17b85b9b4ee6614bc6dd46c08...`
Code that ran	`sha256:derivation-tool-o...`
Forged on	NVIDIA GeForce RTX 5090, 2026-04-08
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