voxyne / README.md
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voxyne v0.1: bf16 base + fp32/int8/int4 ONNX (int4 default) + model card
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metadata
license: cc-by-nc-4.0
language:
  - en
pipeline_tag: text-generation
tags:
  - byte-level
  - conversational
  - rahuketu
  - voxyne
  - int4
  - edge
  - cpu

Voxyne

A tiny (128.8M-param) byte-level conversational language model with the RahuKetu sigma_K control channel. It runs offline on CPU, and quantized to int4 it stays coherent in ~80 MB — the intended default.

Scope — please read. Voxyne is built to converse, not to know. It has an identity and conversational ability; it is not a knowledge base and will make up facts if asked — knowledge is meant to come from external tools/retrieval (a separate system). Judge it on coherence, not factual recall.

Files — int4 is the default

file size use
voxyne-int4.onnx 81 MB DEFAULT — CPU/edge deployment (ONNX Runtime)
voxyne-int8.onnx 129 MB int8 ONNX
voxyne-fp32.onnx 511 MB full-precision ONNX
voxyne-v0.1.pt 258 MB bf16 PyTorch weights (for the voxyne package / fine-tuning)

The ONNX graphs are a single-token decode step with an explicit KV cache (inputs h, pk, pv -> outputs logits, npk, npv); the byte embedding and the sigma_K encoder run outside the graph. See the voxyne package for the decode protocol.

Quick start (PyTorch)

pip install voxyne   # then download voxyne-v0.1.pt from this repo
from voxyne import VoxyneConfig, build, load_weights, generate

model, enc = build(VoxyneConfig())
load_weights(model, "voxyne-v0.1.pt")
print(generate(model, enc, "who are you?", device="cpu"))
# -> "I'm Voxyne, an AI assistant created by Ramakrishnan."

Training-data provenance (why the license)

Voxyne's weights are trained on a mix that includes non-commercial sources, so the weights are released under CC BY-NC 4.0 (non-commercial). Free for research, education, and personal use.

stage sources (examples) license note
pretrain FineWeb-Edu, Cosmopedia, TinyStories permissive / synthetic
grammar WordNet, FrameNet, GoEmotions permissive (attribution)
commonsense ConceptNet, ATOMIC ConceptNet = CC BY-SA
dialogue SODA, UltraChat, OASST2, daily_dialog, empathetic_dialogues, WildChat daily_dialog / empathetic = CC BY-NC; WildChat = AI2 ImpACT
identity author-written original

The code (voxyne package) is Apache-2.0; only the weights are NC. A future clean-data retrain (kalki) will carry Apache-licensed weights.

AI-assistance disclosure

Built by Ramakrishnan (ORCID 0009-0006-0905-7275). AI tools assisted with the training/quantization automation and tooling; the model design, direction, and all decisions are the author's.

License

Weights: CC BY-NC 4.0 (non-commercial). Code: Apache-2.0.