import pandas as pd

# Define the data
data = {
    "Original Name"      : [],
    "Proper Display Name": [],
    "Link"               : [],
}

# Add model information to the
data['Original Name'].append('salmonn_7b')
data['Proper Display Name'].append('SALMONN-7B')
data['Link'].append('https://arxiv.org/html/2310.13289v2')

data['Original Name'].append('wavllm_fairseq')
data['Proper Display Name'].append('WavLLM')
data['Link'].append('https://arxiv.org/abs/2404.00656')

data['Original Name'].append('Qwen2-Audio-7B-Instruct')
data['Proper Display Name'].append('Qwen2-Audio-7B-Instruct')
data['Link'].append('https://arxiv.org/abs/2407.10759')

data['Original Name'].append('whisper_large_v3_with_llama_3_8b_instruct')
data['Proper Display Name'].append('Whisper-Large-v3+Llama-3-8B-Instruct')
data['Link'].append('https://arxiv.org/abs/2406.16020')

data['Original Name'].append('mowe_audio')
data['Proper Display Name'].append('MOWE-Audio')
data['Link'].append('https://arxiv.org/abs/2409.06635')

data['Original Name'].append('qwen_audio_chat')
data['Proper Display Name'].append('Qwen-Audio-Chat')
data['Link'].append('https://arxiv.org/abs/2311.07919')

data['Original Name'].append('meralion_audiollm_v1_lora')
data['Proper Display Name'].append('MERaLion-AudioLLM-v1-LoRA')
data['Link'].append('https://www.a-star.edu.sg/i2r/research/I2RTechs/research/i2r-techs-solutions/unlocking-the-potential-of-large-language-models-(llms)-with-i-r-s-merlion-ai')

data['Original Name'].append('meralion_audiollm_v1_mse')
data['Proper Display Name'].append('MERaLion-AudioLLM-v1-MSE')
data['Link'].append('https://www.a-star.edu.sg/i2r/research/I2RTechs/research/i2r-techs-solutions/unlocking-the-potential-of-large-language-models-(llms)-with-i-r-s-merlion-ai')

data['Original Name'].append('stage2_whisper3_fft_mlp100_gemma2_9b_lora')
data['Proper Display Name'].append('Stage2-Whisper3-FFT-MLP100-Gemma2-9B-LoRA')
data['Link'].append('https://www.a-star.edu.sg/i2r/research/I2RTechs/research/i2r-techs-solutions/unlocking-the-potential-of-large-language-models-(llms)-with-i-r-s-merlion-ai')



def get_dataframe():
    """
    Returns a DataFrame with the data and drops rows with missing values.
    """
    df = pd.DataFrame(data)
    return df.dropna(axis=0)