---

license: other

license_name: nemotron-fable5-derivative

base_model: unsloth/NVIDIA-Nemotron-3-Super-120B-A12B

datasets:

- Glint-Research/Fable-5-traces

library_name: gguf

pipeline_tag: text-generation

tags:

- nemotron

- nemotron_h

- mamba2

- mixture-of-experts

- gguf

- llama.cpp

- lm-studio

- qlora

- reasoning

- agentic

- tool-use

---

Fabletron — Nemotron-3-Super-120B-A12B · Fable-5 (GGUF)

QLoRA fine-tune of NVIDIA Nemotron-3-Super-120B-A12B (120B-total / 12B-active hybrid

Mamba-2 + Latent-MoE, nemotron_h) on the pi_agent split of

Glint-Research/Fable-5-traces,

targeting reasoning, agentic planning, and tool-use. This repo holds the GGUF export for

LM Studio / llama.cpp.

Files

| File | Quant | Size |

|------|-------|------|

| Nemotron-3-Super-120B-fable5-Q4_K_M.gguf | Q4_K_M | ≈80.1 GiB (86.05 GB) |

> Requires a llama.cpp build with nemotron_h_moe support (PR #18058 or later). Recent

> LM Studio runtimes include it. Uses the ChatML template baked into the GGUF.

Training

• Method: QLoRA (4-bit NF4 base) via Unsloth. LoRA r=8, α=16, dropout=0, bias=none.

Targets (by regex) attention q/k/v/o_proj, Mamba-2 in_proj/out_proj, and the

up/down_proj of all 512 routed experts + the shared expert — this MoE is non-gated,

so up/down_proj is the full expert FFN (there is no gate_proj). The MoE router

(mixer.gate, an nn.Parameter) and the MoE-latent fc1/fc2_latent_proj stay frozen.

• Data: Glint-Research/Fable-5-traces, config pi_agent, ChatML, response-only loss.
• Schedule: 1 epoch (248 steps), grad-accum 16, lr 2e-5 cosine + warmup.
• Final training loss: ≈0.74 true per-token CE (final-phase mean; Unsloth logs loss ×

grad-accum, so the raw logged value is ÷16 here).

• Evaluation (held-out Fable-5 pi_agent, 81 rows, base → fine-tuned): cross-entropy

1.12 → 0.78, perplexity 3.07 → 2.18.

• Date: 2026-06-29.
• LoRA adapter (pre-merge) + other formats: greghavens/fabletron-nemotron-3-super-120b.

Provenance & license

This is a derivative of two upstream works, and downstream use must comply with both:

• Base model: NVIDIA Nemotron-3-Super-120B-A12B — see NVIDIA's model license.
• Dataset: Glint-Research/Fable-5-traces — AGPL-3.0, and distilled from Anthropic

Claude outputs (subject to Anthropic's usage terms).

Released as a research artifact. Review the upstream licenses before redistribution or

production use. license: other reflects the combination of the above, not a single license.

Intended use

Research on hybrid Mamba-2/MoE reasoning models, agentic/tool-use experimentation. Not

safety-aligned beyond the base model; evaluate before any production deployment.