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tocsa/atlas-sft

Atlas customer-support triage (capstone, Section 5) โ€” SFT model.

Atlas is a fictional SaaS project-management tool. The model reads an incoming support ticket and returns a category, an urgency, and a short drafted response โ€” the Meridian pattern (eval -> SDG -> SFT -> DPO) applied end-to-end to a new domain during the capstone.

Base model / architecture

nvidia/Mistral-NeMo-Minitron-8B-Instruct (MistralForCausalLM)

Pipeline position

SFT model: a LoRA adapter trained on synthetically generated data, merged into the base model. This is the checkpoint used as the DPO starting point.

Files

  • config.json (702.0B)
  • generation_config.json (111.0B)
  • model.safetensors (15.7GB)
  • special_tokens_map.json (414.0B)
  • tokenizer.json (8.8MB)
  • tokenizer_config.json (173.4KB)

Recorded metrics

baseline_eval.json

  • n: 12

best_sft.json

  • adapter_path: /scratch/capstone_sft/checkpoints/epoch_2_step_56/model
  • epoch: 2

How to load

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("tocsa/atlas-sft")
tokenizer = AutoTokenizer.from_pretrained("tocsa/atlas-sft")

Course context

Produced in the NVIDIA instructor-led workshop "Adding New Knowledge to LLMs" โ€” Designing and building model-customization pipelines for domain workflows.

The workshop's build-time customization workflow:

Stage What it does Tool
Task definition taxonomy, schema, success criteria
Eval measure target behavior vLLM
Gap evidence baseline + ICL ceiling
Synthetic data targeted examples NeMo Data Designer
Curation quality + dedup NeMo Curator
SFT LoRA task behavior NeMo AutoModel + PEFT
Serve + eval compare model stages vLLM
DPO preference behavior NeMo RL
Model artifact adapter or DPO model

Open-model ecosystem used across the workshop:

Models Data Training Serving
Nemotron NeMo Data Designer NeMo AutoModel vLLM
Open weights NeMo Curator LoRA / PEFT NGC containers
Teacher models Hugging Face NeMo RL Local eval

Training data for this run was synthetically generated (NeMo Data Designer) and/or curated during the workshop exercises. Educational artifact โ€” not reviewed for production use.

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