Update README.md

README.md

@@ -7,52 +7,17 @@ tags:
 - trl
 - sft
 licence: license
+language:
+- ko
+- en
 ---
 
-# Model Card for exaone-3.5-2.4b-instruct-dacon-llm
+# Model Details
 
-This model is a fine-tuned version of [LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct).
-It has been trained using [TRL](https://github.com/huggingface/trl).
+**EXAONE-3.5-2.4B-it-DACON-LLM**
 
-## Quick start
+[난독화된 한글 리뷰 복원 AI 경진대회](https://dacon.io/competitions/official/236446/overview/description)
 
-```python
-from transformers import pipeline
+**Model developers** Dongwook Min (mindw96)
 
-question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
-generator = pipeline("text-generation", model="mindw96/exaone-3.5-2.4b-instruct-dacon-llm", device="cuda")
-output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
-print(output["generated_text"])
-```
-
-## Training procedure
-
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/mindw96/huggingface/runs/ekv0pcwp) 
-
-
-This model was trained with SFT.
-
-### Framework versions
-
-- TRL: 0.13.0
-- Transformers: 4.48.0
-- Pytorch: 2.5.1+cu124
-- Datasets: 3.2.0
-- Tokenizers: 0.21.0
-
-## Citations
-
-
-
-Cite TRL as:
-    
-```bibtex
-@misc{vonwerra2022trl,
-	title        = {{TRL: Transformer Reinforcement Learning}},
-	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
-	year         = 2020,
-	journal      = {GitHub repository},
-	publisher    = {GitHub},
-	howpublished = {\url{https://github.com/huggingface/trl}}
-}
-```
+**Model Release Date** 15.01.2025.