phi3-nl2bash-lora

This repository contains LoRA adapter weights fine-tuned on the jiacheng-ye/nl2bash dataset to convert natural language instructions into Linux bash commands.

⚠️ This repository contains LoRA adapters only, not the base model.
You must load these adapters on top of
microsoft/phi-3-mini-128k-instruct.

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Intended use

The model is trained to output only valid bash commands, with no explanations.

Example

Input:

List all .txt files recursively and count lines

Output:

find . -name "*.txt" | xargs wc

Training summary

• Base model: microsoft/phi-3-mini-128k-instruct
• Fine-tuning method: LoRA (PEFT)
• Trainer: TRL SFTTrainer
• Dataset: jiacheng-ye/nl2bash
• Output format: Bash commands only

Loading example

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

base_model = "microsoft/phi-3-mini-128k-instruct"
lora_model = "ayertiam/phi3-nl2bash-lora"

tokenizer = AutoTokenizer.from_pretrained(base_model, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    base_model,
    torch_dtype=torch.bfloat16,
    device_map="auto",
    trust_remote_code=True
)

model = PeftModel.from_pretrained(model, lora_model)
model.eval()

Notes

• These adapters are model-specific and only compatible with microsoft/phi-3-mini-128k-instruct.
• For Ollama or GGUF usage, the LoRA must be merged into the base model and converted before inference as done here https://huggingface.co/ayertiam/phi3-nl2bash-gguf