Instructions to use otavio-lemos/oci-copilot-jr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use otavio-lemos/oci-copilot-jr with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir oci-copilot-jr otavio-lemos/oci-copilot-jr
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
Model Card: otavio-lemos/oci-copilot-jr
Overview
OCI Copilot Jr is a fine-tuned Large Language Model specialized in Oracle Cloud Infrastructure (OCI) operations. Built on Qwen 2.5 Coder 7B Instruct and fine-tuned using LoRA on Apple Silicon (M3 Pro).
| Attribute | Value |
|---|---|
| Base Model | Qwen2.5-Coder-7B-Instruct-4bit |
| Fine-tuning Method | LoRA (Rank 32, Alpha 64) |
| Framework | MLX-Tune 0.4.18 |
| Hardware | Apple Silicon M3 Pro (18GB) |
| Training Date | April 2026 |
Training Configuration
{
"model": "mlx-community/Qwen2.5-Coder-7B-Instruct-4bit",
"train_data": "data/train.jsonl",
"valid_data": "data/valid.jsonl",
"output_dir": "outputs/cycle-1",
"batch_size": 1,
"learning_rate": 1e-4,
"lora_rank": 32,
"lora_alpha": 64,
"lora_dropout": 0.05,
"gradient_accumulation": 4,
"num_layers": 16,
"target_modules": ["q_proj","k_proj","v_proj","o_proj","gate_proj","up_proj","down_proj"],
"iters": 2475,
"max_seq_length": 1024,
"val_batches": 5,
"eval_steps": 247,
"logging_steps": 1,
"save_steps": 247,
"warmup_steps": 247,
"gradient_checkpointing": false,
"lr_scheduler": "cosine",
"weight_decay": 0.01,
"seed": 42,
"gradient_clip_norm": 1.0,
"bf16": true
}
Dataset
- Training: 9,897 examples (75%)
- Validation: 1,979 examples (15%)
- Evaluation: 1,320 examples (10%)
- Total: 13,196 examples
- Language: Portuguese (pt)
- Categories: 88 OCI domains
Benchmark Results (Cycle 1)
Evaluation on 200 samples comparing base model vs fine-tuned:
| Metric | Base Model | Fine-Tuned | Delta |
|---|---|---|---|
| Technical Correctness | 3.67 | 4.51 | +0.84 |
| Depth | 3.11 | 3.93 | +0.82 |
| Structure | 3.47 | 4.45 | +0.98 |
| Hallucination | 3.23 | 3.95 | +0.72 |
| Clarity | 3.07 | 3.06 | -0.01 |
| Overall | 3.31 | 3.98 | +0.67 |
Top Performance Gains by Category
| Rank | Category | Delta |
|---|---|---|
| 1 | Security Posture Management | +2.24 |
| 2 | Governance Tagging | +2.20 |
| 3 | Terraform State | +2.00 |
| 4 | Troubleshooting Functions | +1.86 |
| 5 | Security WAF | +1.84 |
Benchmark Charts
Usage
MLX (Apple Silicon - Recommended)
mlx_lm.server --model mlx-community/Qwen2.5-Coder-7B-Instruct-4bit --adapter outputs/cycle-1/adapters
Ollama
# Create Modelfile
cat > Modelfile << 'EOF'
FROM ./oci-copilot-jr-Q4_K_M.gguf
PARAMETER temperature 0.1
PARAMETER top_p 0.9
PARAMETER top_k 40
SYSTEM Você é um especialista em OCI (Oracle Cloud Infrastructure).
EOF
ollama create oci-copilot-jr -f Modelfile
llama.cpp
llama-server -m oci-copilot-jr-Q4_K_M.gguf --port 8080
System Prompt
Você é um arquiteto e especialista experiente em OCI. Forneça orientações técnicas, profundas e definitivas com:
- Comandos OCI CLI reais
- Trechos de código Terraform
- Passos detalhados e justificação
- Restrições do cenário observadas
- Checklist de pré-requisitos
Limitations
- Language: Optimized for Brazilian Portuguese (PT-BR)
- Scope: Operational guidance — OCI CLI commands, Terraform snippets, step-by-step procedures, risk validation, and troubleshooting runbooks
- Training: Single-cycle LoRA (may improve with more cycles)
- Knowledge: Based on OCI documentation up to April 2026
Citation
@model{lemos_2026_oci_copilot_jr,
author = {Otavio Lemos},
title = {OCI Copilot Jr},
year = {2026},
publisher = {HuggingFace},
url = {https://huggingface.co/otavio-lemos/oci-copilot-jr}
}
License
MIT License - See LICENSE
Fine-tuned on Apple Silicon M3 Pro using MLX-Tune
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

