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

python

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.

samuelstolicny/claudie-expert-gemma4-26b-a4b

Claudie Expert — Gemma 4 31B

About Claudie