--- license: cc-by-nc-sa-4.0 datasets: - wi_locness - matejklemen/falko_merlin - paws - paws-x - asset language: - en - de - es - ar - ja - ko - zh metrics: - bleu - rouge - sari - accuracy library_name: transformers --- # Model Card for mEdIT-xxl The `medit-xxl` model was obtained by fine-tuning the `MBZUAI/bactrian-x-llama-13b-lora` model on the mEdIT dataset. **Paper:** mEdIT: Multilingual Text Editing via Instruction Tuning **Authors:** Vipul Raheja, Dimitris Alikaniotis, Vivek Kulkarni, Bashar Alhafni, Dhruv Kumar ## Model Details ### Model Description - **Language(s) (NLP)**: Arabic, Chinese, English, German, Japanese, Korean, Spanish - **Finetuned from model:** `MBZUAI/bactrian-x-llama-13b-lora` ### Model Sources - **Repository:** https://github.com/vipulraheja/medit - **Paper:** TBA ## How to use ### Instruction format Adherence to the following instruction format is essential; failure to do so may result in the model producing less-than-ideal results. ``` instruction_tokens = [ "Instruction", "Anweisung", ... ] input_tokens = [ "Input", "Aporte", ... ] output_tokens = [ "Output", "Produzione", ... ] task_descriptions = [ "Fix grammatical errors in this sentence", # <-- GEC task "Umschreiben Sie den Satz", # <-- Paraphrasing ... ] The entire list of possible instruction, input, output tokens, and task descriptions can be found in the Appendix of our paper. prompt_template = """### :\n\n### :\n\n### :\n\n""" Note that the tokens and the task description need not be in the language of the input. ``` ### Run the model ```python from transformers import AutoTokenizer, AutoModelForCausalLM model_id = "grammarly/medit-xxl" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id) # English GEC prompt = '### 命令:\n文章を文法的にする\n### 入力:\nI has small cat ,\n### 出力:\n\n' inputs = tokenizer(prompt, return_tensors='pt') outputs = model.generate(**inputs, max_new_tokens=20) print(tokenizer.decode(outputs[0], skip_special_tokens=True) # --> I have a small cat , # German GEC prompt = '### 命令:\n文章を文法的にする\n### 入力:\nIch haben eines kleines Katze ,\n### 出力:\n\n' # ... # --> Ich habe eine kleine Katze , ```