Vakamalla123-Anitha

oracle19c-nl2sql-granite-4.1-3b-lora

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README

License: apache-2.0

Base model

This repository contains a LoRA adapter, not a full standalone model.

Load it together with:

ibm-granite/granite-4.1-3b

Intended use

Convert natural-language questions into Oracle 19c SQL
Generate analytical and reporting queries
Support SQL learning, prototyping, and evaluation
Use with a schema-retrieval or RAG layer for better table and column selection

Training details

Base model: Granite 4.1 3B Instruct
Fine-tuning method: 4-bit NF4 QLoRA with double quantization
Training approach: Supervised fine-tuning with PEFT LoRA
Training examples: 3,200 total
- 2,800 Oracle-focused NL→SQL examples
- 400 general-SQL replay examples
Validation examples: 350
Epochs: 1
Training steps: 400
Learning rate: 2e-5
Maximum sequence length: 1,024
Per-device batch size: 1
Gradient accumulation steps: 8
Effective batch size: 8
Compute precision: FP16
Training hardware: Tesla T4 GPU

LoRA configuration

Rank: 16
Alpha: 32
Dropout: 0.05
Target modules: q_proj, k_proj, v_proj, o_proj
PEFT version: 0.20.0

Limitations and safe use

This adapter is not a database-security system.
Review every generated SQL query before running it.
Use read-only database access for analytics workloads.
Apply authentication, authorization, tenant, organization, role, and row-level filters in your application.
Test generated SQL against your own schema and Oracle version.
The training examples are generalized and do not include real customer records, credentials, or database connections.

Load the adapter

python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model_id = "ibm-granite/granite-4.1-3b"
adapter_id = "Vakamalla123-Anitha/oracle19c-nl2sql-granite-4.1-3b-lora"

tokenizer = AutoTokenizer.from_pretrained(base_model_id)

base_model = AutoModelForCausalLM.from_pretrained(
    base_model_id,
    torch_dtype=torch.float16,
    device_map="auto"
)

model = PeftModel.from_pretrained(base_model, adapter_id)

Example

Question

text
Show total sales by sales representative for July 2026.

Expected behavior

Generate an Oracle SQL SELECT query with date filtering, aggregation, and grouping. Always review the generated SQL before execution.

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Dedicated Endpoints

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Model Details

Model Provider

Vakamalla123-Anitha

Model Tree

Base

ibm-granite/granite-4.1-3b

Adapter

this model

Input Modalities

Text

Output Modalities