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NotIshaan/
ernie-arduino-qa-unsloth-v2

baidu/ERNIE-4.5-0.3B-PT

finetune

apache-2.0

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ERNIE Arduino Q&A Model

Model Description

This is an ERNIE model fine-tuned on Arduino documentation using Unsloth for the AI Challenge. The model is specifically optimized to answer questions about Arduino programming, libraries, hardware, and best practices.

Training Details

Base Model: baidu/ERNIE-4.5-0.3B-PT
Fine-tuning Method: Unsloth with LoRA
Dataset: Arduino training instruction dataset (17,944 samples)
Hardware: NVIDIA T4 GPU
Training Time: 7591.14 seconds
Final Training Loss: 1.1063

Hyperparameters

Learning Rate: 0.0005
Epochs: 2
Batch Size: 2
Gradient Accumulation Steps: 8
LoRA Rank: 32
LoRA Alpha: 64
Max Sequence Length: 1024
Quantization: 4-bit

Usage

python

from unsloth import FastLanguageModel

# Load model
model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="NotIshaan/ernie-arduino-qa-unsloth-v2",
    max_seq_length=1024,
    dtype=None,
    load_in_4bit=True,
)
FastLanguageModel.for_inference(model)

# Generate response
instruction = "What is Arduino?"
prompt = f'''Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{instruction}

### Response:
'''

inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7)
response = tokenizer.batch_decode(outputs)[0]
print(response)

Example Outputs

Question: "How do I use digitalWrite in Arduino?"

Answer: The model provides detailed explanations of Arduino functions, syntax, and best practices.

Limitations

Trained specifically on Arduino documentation
May not generalize well to other programming domains
Responses limited to information present in training data

Citation

If you use this model, please cite:

bibtex

@misc{ernie-arduino-qa,
  author = {Ishaan Pandey},
  title = {ERNIE Arduino Q&A Model},
  year = {2024},
  publisher = {Hugging Face},
  url = {https://huggingface.co/NotIshaan/ernie-arduino-qa-unsloth-v2}
}

Acknowledgments

Unsloth for efficient fine-tuning framework
ERNIE team for the base model
Arduino community for documentation