mevsg/rumi-correction-v1

Model Card for Model ID

Model Details

Model Description

This model is trained with QLoRA with parameters r = lora_alpha = 4.

• Developed by: hyhyhyhyyhyh
• Model type: Gemma 2 9B
• Language(s) (NLP): Malay, English
• License: [More Information Needed]
• Finetuned from model aisingapore/Gemma-SEA-LION-v3-9B-IT

Model Sources [optional]

• Repository: [More Information Needed]
• Paper [optional]: [More Information Needed]
• Demo [optional]: [More Information Needed]

How to Get Started with the Model

Use the code below to get started with the model:

from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer

trained_model = AutoModelForCausalLM.from_pretrained(
    "culturalheritagenus/rumi-correction-v1.1",
    device_map="auto",
    torch_dtype=torch.bfloat16
)
trained_tokenizer = AutoTokenizer.from_pretrained("culturalheritagenus/rumi-correction-v1.1")

To perform inference:

messages = [
    {"role": "user", "content": "You are a Malay language spelling corrector. I will give you some text written in messy Rumi (shortened or mistyped). Rewrite it in correct Malay Rumi spelling.\naurng ank. yngdim dimn anm aurngdan"},
]
inputs = tokenizer.apply_chat_template(
    messages,
    tokenize = True,
    add_generation_prompt = True, # Must add for generation
    return_tensors = "pt",
).to("cuda")


text_streamer = TextStreamer(tokenizer)
_ = trained_model.generate(input_ids = inputs, streamer = text_streamer, max_new_tokens = 128, use_cache = True)

Training Details

Training Data

The model was trained on culturalheritagenus/rumi-correction-v1.1-data-v3

Training Procedure

To replicate this model, please refer to the provided script and below. Ensure that the versions of all languages and libraries are the same.

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• Hardware Type: 1x GH200 (96 GB)
• Hours used: ~12
• Cloud Provider: Lambda
• Compute Region: US-East (Lambda Labs)

Technical Specifications

Software

• Python version: 3.10.12
• CUDA version: 12.8
• Torch version: 2.7.1+cu128

Citation [optional]

BibTeX:

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APA:

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Model Card Authors [optional]

hyhyhyhyyhyh