AI Translator Eng To 9ja

🚀 AI-translator-eng-to-9ja

這個模型是一個擁有4.18億參數的翻譯模型，專為將英語翻譯成約魯巴語、伊博語和豪薩語而構建。它在包含150萬條句子（每種語言50萬條）的數據集上進行訓練，能夠為這些語言提供高質量的翻譯。構建該模型的初衷是打造一個系統，讓使用伊博語、豪薩語和約魯巴語與大語言模型（LLMs）進行交流變得更加容易。

🚀 快速開始

要使用此模型進行翻譯任務，你可以從Hugging Face的transformers庫中加載它：

from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer

import huggingface_hub
huggingface_hub.login()


# Load the fine-tuned model
model = M2M100ForConditionalGeneration.from_pretrained("HelpMumHQ/AI-translator-eng-to-9ja")
tokenizer = M2M100Tokenizer.from_pretrained("HelpMumHQ/AI-translator-eng-to-9ja")

# translate English to Igbo
eng_text="Healthcare is an important field in virtually every society because it directly affects the well-being and quality of life of individuals. It encompasses a wide range of services and professions, including preventive care, diagnosis, treatment, and management of diseases and conditions."
tokenizer.src_lang = "en"
tokenizer.tgt_lang = "ig"
encoded_eng = tokenizer(eng_text, return_tensors="pt")
generated_tokens = model.generate(**encoded_eng, forced_bos_token_id=tokenizer.get_lang_id("ig"))
tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)



# translate English to yoruba
eng_text="Healthcare is an important field in virtually every society because it directly affects the well-being and quality of life of individuals. It encompasses a wide range of services and professions, including preventive care, diagnosis, treatment, and management of diseases and conditions. Effective healthcare systems aim to improve health outcomes, reduce the incidence of illness, and ensure that individuals have access to necessary medical services."
tokenizer.src_lang = "en"
tokenizer.tgt_lang = "yo"
encoded_eng = tokenizer(eng_text, return_tensors="pt")
generated_tokens = model.generate(**encoded_eng, forced_bos_token_id=tokenizer.get_lang_id("yo"))
tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)

# translate English to Hausa
eng_text="Healthcare is an important field in virtually every society because it directly affects the well-being and quality of life of individuals. It encompasses a wide range of services and professions, including preventive care, diagnosis, treatment, and management of diseases and conditions. Effective healthcare systems aim to improve health outcomes, reduce the incidence of illness, and ensure that individuals have access to necessary medical services."
tokenizer.src_lang = "en"
tokenizer.tgt_lang = "ha"
encoded_eng = tokenizer(eng_text, return_tensors="pt")
generated_tokens = model.generate(**encoded_eng, forced_bos_token_id=tokenizer.get_lang_id("ha"))
tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)

✨ 主要特性

• 支持的語言：
  • 源語言：英語
  • 目標語言：約魯巴語、伊博語、豪薩語

📦 安裝指南

文檔未提及安裝相關內容，跳過該章節。

💻 使用示例

基礎用法

# 上述使用此模型進行翻譯任務的代碼示例
from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer

import huggingface_hub
huggingface_hub.login()


# Load the fine-tuned model
model = M2M100ForConditionalGeneration.from_pretrained("HelpMumHQ/AI-translator-eng-to-9ja")
tokenizer = M2M100Tokenizer.from_pretrained("HelpMumHQ/AI-translator-eng-to-9ja")

# translate English to Igbo
eng_text="Healthcare is an important field in virtually every society because it directly affects the well-being and quality of life of individuals. It encompasses a wide range of services and professions, including preventive care, diagnosis, treatment, and management of diseases and conditions."
tokenizer.src_lang = "en"
tokenizer.tgt_lang = "ig"
encoded_eng = tokenizer(eng_text, return_tensors="pt")
generated_tokens = model.generate(**encoded_eng, forced_bos_token_id=tokenizer.get_lang_id("ig"))
tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)

# 其他語言翻譯代碼同理

📚 詳細文檔

支持的語言代碼

• 英語：en
• 約魯巴語：yo
• 伊博語：ig
• 豪薩語：ha

訓練數據集

訓練數據集包含150萬對翻譯數據，這些數據來自開源平行語料庫和針對約魯巴語、伊博語和豪薩語精心策劃的數據集的組合。

侷限性

• 雖然該模型在英語到約魯巴語、伊博語和豪薩語的翻譯中表現良好，但性能可能會因文本的複雜性和領域而異。
• 對於極長的句子或有歧義的上下文，翻譯質量可能會下降。

訓練超參數

訓練過程中使用了以下超參數：

• 學習率：2e - 05
• 訓練批次大小：64
• 評估批次大小：64
• 隨機種子：42
• 優化器：Adam（β1 = 0.9，β2 = 0.999，ε = 1e - 08）
• 學習率調度類型：線性
• 訓練輪數：3

框架版本

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1

🔧 技術細節

文檔未提供足夠詳細的技術實現細節，跳過該章節。

📄 許可證

該模型採用MIT許可證。