samuelstolicny/claudie-expert-gemma4-31b

Claudie Expert — Gemma 4 31B

Fine-tuned Gemma 4 31B-IT specialized on Claudie — an open-source platform for managing multi-cloud and hybrid-cloud Kubernetes infrastructure.

About Claudie

Claudie provisions and manages Kubernetes clusters declaratively across AWS, Azure, GCP, OCI, Hetzner, Exoscale, CloudRift, and OpenStack via the InputManifest CRD. Built by Berops.

• Project: github.com/berops/claudie
• Documentation: docs.claudie.io/latest

What this model knows

This model was fine-tuned on ~8,000 Claudie-specific Q&A conversations covering:

• Claudie's 8 microservices (Manager, Terraformer, Ansibler, Kube-Eleven, Kuber, Claudie-Operator, Autoscaler-Adapter)
• InputManifest CRD authoring for multi-cloud / GPU / autoscaling clusters
• Debugging stuck states, NATS consumer lag, Terraform state locks, WireGuard issues
• gRPC service communication, state machine, reconciliation loops
• Claudie architecture, data flow between services
• Kubernetes integration patterns

Files in this repo

File	Purpose
model-*.safetensors	Merged bf16 weights (for vLLM, Transformers)
*.Q4_K_M.gguf	4-bit GGUF (for Ollama, llama.cpp)
chat_template.jinja	Gemma 4 chat template

Usage

vLLM

vllm serve samuelstolicny/claudie-expert-gemma4-31b --max-model-len 8192

Ollama

ollama run hf.co/samuelstolicny/claudie-expert-gemma4-31b:Q4_K_M

Transformers

from transformers import pipeline
pipe = pipeline("text-generation", model="samuelstolicny/claudie-expert-gemma4-31b")
print(pipe([{"role": "user", "content": "How do I add a GPU node pool in Hetzner?"}]))

Training

• Base model: unsloth/gemma-4-31B-it
• Method: LoRA bf16 (rank 64, alpha 128, all-linear)
• Framework: Unsloth
• Dataset: 8,012 synthetic Q&A conversations generated from the Claudie codebase + docs
• Hardware: 1x RTX PRO 6000 96GB

License

Apache 2.0 — same as the base model and Claudie.