---
license: apache-2.0
base_model: Qwen/Qwen3-4B
library_name: transformers
pipeline_tag: text-generation
tags:
- qwen3
- qlora
- rag
- grounded-generation
- citations
- mining
- blasting
- safety-data-sheets
---

# dyno-blast-4b

A QLoRA fine-tune of **Qwen3-4B** that answers blasting / explosives technical and
safety questions **strictly from retrieved context**, attaches `[N]` + page
citations to every claim, and **refuses when the answer isn't in the provided
sources**.

This is the *generation* half of a grounded RAG system over Dyno Nobel Australia's
public technical literature (product technical data sheets, Safety Data Sheets,
application guides, case studies). **Facts live in the retriever; the model learns
the behavior** — cite, ground, refuse. Companion vector DB:
[`kcherry497/dyno-blast-4b-rag`](https://huggingface.co/datasets/kcherry497/dyno-blast-4b-rag).

## Intended use & limitations
Retrieval-augmented Q&A for mining / quarry / blasting professionals. **Not a
standalone knowledge source** — use with the retriever (intfloat/e5-base-v2 + a
Qdrant collection). For SDS / safety content, always verify against the cited
source PDF; the model is trained to give page numbers for exactly this reason.
Domain-specific to Dyno Nobel AU products.

## Training
- **Base:** Qwen/Qwen3-4B
- **Method:** QLoRA (4-bit nf4), r=16, α=32, dropout=0.05, targets all attn + MLP projections
- **Data:** **1,674 synthetic grounded examples** — 1,656 `[N]`-cited answers + 18 refusal / safe-decline examples — generated by a teacher over retrieved context, covering SDS sections, technical specs, application/case-study/brochure topics, Explosive Engineers Guide articles, industrial chemicals, and blast calculators
- **Schedule:** 3 epochs, lr 1e-4 cosine, full-sequence SFT
- **Result:** final `train_loss` **0.97**

Retrieval corpus (companion dataset repo): **3,819 chunks across 682 documents** —
dynonobel.com.au + dynonobel.com (126 products) + the Explosive Engineers Guide app
(4 regions) + Industrial Chemicals + resource-centre case studies/guides/brochures +
blast calculators.

## Files
- `*.safetensors` — merged fp16 weights (load with `transformers`)
- `dyno-blast-4b-q8_0.gguf` — q8_0 GGUF for llama.cpp / Ollama

## Prompt format
Grounded system prompt (answer only from numbered SOURCEs, cite `[N]`, refuse if
absent) + numbered `SOURCE [N]` blocks from the retriever, then the question. The
exact system prompt and chunk schema are in the companion dataset repo.