Scibert

# download_scibert.py
# This script downloads and loads the SciBERT model from Hugging Face.

from transformers import AutoTokenizer, AutoModel
import torch

def load_scibert():
    """
    Downloads and loads the SciBERT model from Hugging Face.
    Model: allenai/scibert_scivocab_uncased
    """
    model_name = "allenai/scibert_scivocab_uncased"

    print(f"🔽 Downloading and loading model: {model_name}")

    # Load tokenizer
    tokenizer = AutoTokenizer.from_pretrained(model_name)

    # Load model (set torch_dtype to auto for device optimization)
    model = AutoModel.from_pretrained(model_name, torch_dtype="auto")

    print("✅ SciBERT model and tokenizer successfully loaded!")
    return tokenizer, model

if __name__ == "__main__":
    tokenizer, model = load_scibert()

    # Test encoding
    text = "Artificial intelligence is revolutionizing scientific research."
    inputs = tokenizer(text, return_tensors="pt")
    with torch.no_grad():
        outputs = model(**inputs)

    print("🔍 Model output shape:", outputs.last_hidden_state.shape)