import torch
from transformers import AutoTokenizer, AutoModel
from huggingface_hub import hf_hub_download

# Download model
model_path = hf_hub_download(
    repo_id="george121212afasf/model",
    filename="best_model.pt"
)

# Load checkpoint
checkpoint = torch.load(model_path, map_location='cpu')

# Get tokenizer
tokenizer = AutoTokenizer.from_pretrained("indobenchmark/indobert-base-p1")

# Your model class and inference code here

Training Data

Trained on annotated Indonesian sports news articles from various sources.

Model Size

Parameters: ~125M (IndoBERT base)
File size: ~1420 MB

Intended Use

This model is designed for extracting sports-related entities from Indonesian news articles, particularly for:

Sports journalism analysis
Automated content tagging
Information extraction from sports news
5W1H (Who, What, When, Where, Why, How) analysis

Limitations

Optimized for Indonesian language sports content
Best performance on football, basketball, and badminton articles
May not generalize well to other sports domains

Contact

For questions or feedback, please open an issue in the repository.