hamtaai / e5-large-instruct-hadith

hamtaai/e5-large-instruct-hadith

This is a fine-tuned version of intfloat/multilingual-e5-large-instruct specifically optimized for Persian and Arabic text processing and question-answering tasks.

Model Description

This model has been fine-tuned on a comprehensive dataset of Persian and Arabic religious texts, including:

• Persian and Arabic religious texts including Hadith collections

The model is particularly effective for:

• Semantic search in Persian and Arabic texts
• Question-answering tasks
• Information retrieval
• Cross-lingual understanding between Persian and Arabic

Training Configuration

• Base Model : intfloat/multilingual-e5-large-instruct
• Epochs : 5
• Batch Size : 72
• Learning Rate : 2e-05
• Warmup Steps Ratio : 0.1
• Evaluation Steps Ratio : 0.5

Usage

Using Sentence-Transformers

from sentence_transformers import SentenceTransformer

# Load the model
model = SentenceTransformer('hamtaai/e5-large-instruct-hadith')

# For instruct models, use proper prefixes
query = "query: سوال شما اینجا"
passage = "passage: متن پاسخ اینجا"

# Encode texts
query_embedding = model.encode(query)
passage_embedding = model.encode(passage)

# Calculate similarity
from sentence_transformers.util import cos_sim
similarity = cos_sim(query_embedding, passage_embedding)

Using Hugging Face Transformers

from transformers import AutoTokenizer, AutoModel
import torch

tokenizer = AutoTokenizer.from_pretrained('hamtaai/e5-large-instruct-hadith')
model = AutoModel.from_pretrained('hamtaai/e5-large-instruct-hadith')

# Tokenize and encode
inputs = tokenizer("متن شما", return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs)
    embeddings = outputs.last_hidden_state.mean(dim=1)

Performance

This model has been optimized for Persian and Arabic text processing and shows improved performance on:

• Semantic similarity tasks
• Question-answering accuracy
• Cross-lingual retrieval
• Religious text understanding

Training Data

The model was trained on a curated dataset of Persian and Arabic religious texts, including:

• Hadith collections
• Quranic commentaries (Tafsir)
• Religious question-answer pairs
• Contextual information for better understanding

Limitations

• Primarily optimized for Persian and Arabic texts
• Performance may vary on other languages
• Best results achieved with proper text normalization
• Requires appropriate prefixes for instruct-based models

Citation

If you use this model, please cite the original base model and mention this fine-tuned version:

@misc{hamtaai/e5_large_instruct_hadith,
  title={hamtaai/e5-large-instruct-hadith: Fine-tuned Multilingual E5 Model for Persian and Arabic Text Processing},
  author={Your Name},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/hamtaai/e5-large-instruct-hadith}}
}

License

This model is released under the Apache 2.0 License.