continuum-ai/qwen3.5-4b-general-forged
0% Smaller, +29.3% Better
Qwen3.5-4B pruned by 0% and retrained for general through Experiential Plasticity.
15.64 → 11.05 perplexity · 1 cycles
<p align="center"> <a href="https://cambriantech.github.io/forge-alloy/verify/#86000c4ca4a65fe8"> <img src="alloy-qr.png" alt="Verify Chain of Custody" width="160"/> </a> </p>
<p align="center"> <a href="https://cambriantech.github.io/forge-alloy/verify/#86000c4ca4a65fe8"><b>Every claim on this card is verified</b></a><br> <b>Trust: self-attested</b> · 1 benchmark · 1 device tested<br> <a href="https://github.com/CambrianTech/forge-alloy">ForgeAlloy</a> chain of custody · <a href="qwen3.5-4b-general-forged.alloy.json">Download alloy</a> · Merkle-chained </p>
Qwen3.5-4B 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/qwen3.5-4b-general-forged",
torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("continuum-ai/qwen3.5-4b-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 1 cycle on NVIDIA GeForce RTX 5090.
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.
<p align="center"> <a href="https://github.com/CambrianTech/continuum"><img src="https://raw.githubusercontent.com/CambrianTech/continuum/main/docs/images/factory.png" alt="Continuum Model Factory" width="400"/></a> </p>
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
