eschaton-terraform-savant-v0.4.19-gguf/README.md

language, license, base_model, tags, pipeline_tag, inference

language	license	base_model	tags	pipeline_tag	inference
en de	apache-2.0	Qwen/Qwen2.5-Coder-7B-Instruct	terraform hcl iac savant gguf llama-cpp ollama eschaton eu-ai-act annex-iv narrow-domain	text-generation	false

Eschaton Terraform Savant v0.4.19 — GGUF

GGUF-quantized build of ljawadi/eschaton-terraform-savant-v0.4.19 with the LoRA merged into the base, so the model loads directly in llama.cpp, Ollama, LM Studio, text-generation-webui, and any other runtime that consumes GGUF — no GPU required.

For training methodology, evals, EU AI Act Annex IV compliance pack, limitations, and citation, see the main repo.

Available quantizations

File	Size	Use case
eschaton-terraform-savant-v0.4.19-Q4_K_M.gguf	~4.4 GB	Laptop CPU, 8 GB GPU (RTX 3070 / A2000), Apple Silicon M1/M2
eschaton-terraform-savant-v0.4.19-Q5_K_M.gguf	~5.1 GB	Better quality, 12 GB GPU (RTX 3060 / 4070)
eschaton-terraform-savant-v0.4.19-Q8_0.gguf	~7.5 GB	Near-lossless, 16+ GB GPU / Apple Silicon 16 GB+

Ollama

ollama run hf.co/ljawadi/eschaton-terraform-savant-v0.4.19-gguf:Q4_K_M

Then prompt:

>>> Write the complete Terraform HCL code for an aws_s3_bucket 'logs-prod' in eu-central-1
   with versioning, SSE-S3, public-access blocked. Output ONLY HCL in a fenced code block.

The model is trained to refuse non-Terraform tasks. By design (see main repo).

llama.cpp

./llama-cli -m eschaton-terraform-savant-v0.4.19-Q4_K_M.gguf \
  -p "<|im_start|>user\nWrite the Terraform HCL for an aws_s3_bucket 'logs-prod' \
in eu-central-1 with versioning, SSE-S3, public-access blocked. Output ONLY HCL in \
a fenced code block.<|im_end|>\n<|im_start|>assistant\n" \
  -n 1024 --temp 0 --no-display-prompt

LM Studio / text-generation-webui

Drop any of the .gguf files into the models folder and select it from the UI. Use the Qwen2.5 chat template (built into both UIs).

Out of scope — refuses by design

Like the main repo, this savant is only for Terraform HCL. Asking it anything else (python, kubernetes, dockerfile, general questions, even "explain Terraform CI/CD in GitHub Actions") will trigger the canonical refusal:

"I am a Terraform savant. This task is out of scope. Please ask Terraform/HCL questions only."

That refusal score of 1.00 on the held-out OOS bench + 1.00 on a 10-prompt adversarial functional test is the auditable evidence for the Annex IV §3 intended-use declaration.

Contact

eschatonai.eu (website may not be reachable yet — DM LinkedIn)

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🇩🇪 Deutsche Kurzversion

GGUF-quantisierter Build von ljawadi/eschaton-terraform-savant-v0.4.19. Die LoRA ist in die Base gemerged, sodass das Modell direkt in llama.cpp, Ollama, LM Studio etc. lädt — kein GPU nötig.

Für Methodik, Evals, Annex IV Pack und Limitations siehe den Haupt-Repo.

Drei Quantization-Stufen: Q4_K_M (Laptop, ~4.4 GB), Q5_K_M (besser, ~5.1 GB), Q8_0 (near-lossless, ~7.5 GB).

Ollama: ollama run hf.co/ljawadi/eschaton-terraform-savant-v0.4.19-gguf:Q4_K_M

Out of scope: Das Modell lehnt alle Nicht-Terraform-Anfragen ab. Refusal-Score 1.00 perfekt — das ist die auditierbare Evidenz für die Annex-IV-§3-Intended-Use-Deklaration.

Kontakt: eschatonai.eu (ggf. noch nicht erreichbar — DM auf LinkedIn)