religious_org_v1

repo_id = 'GivingTuesday/religious_org_v1'
from huggingface_hub import snapshot_download
snapshot_download(repo_id)

# snapshot_download will return / print a location for the model. Pass that into the function below.
from transformers import pipeline
# 1. Define the local path to your downloaded model directory
# Replace './my_local_model_directory' with the actual path on your machine
model_path = './my_local_model_directory' # copied from output of previous cell

# 2. Load the text classification pipeline from the local directory
# The 'pipeline' function automatically loads the model, tokenizer, and config
# from the specified local path.
try:
    classifier = pipeline(
        task="text-classification",
        model=model_path,
        tokenizer=model_path
    )
    print(f"Model loaded successfully from {model_path}")
except Exception as e:
    print(f"Error loading model: {e}")
    print("Please ensure the directory contains the model weights, config, and tokenizer files.")
    exit()

# 3. Define the string(s) you want to classify
sentences = [
    """St. John's Episcopal is a really beautiful community that preaches "faith in action" -- they welcome and assist migrants, partner with community organizations, run a housing first apartment building for unhoused folks, and they are part of the Together Colorado coalition of faith-based organizations that lobbies for anti-poverty legislation. Bonus: the cathedral is gorgeous and historic.""",
    """I’m atheist but rehearse in a community choir at Christ Church United Methodist and they have pro LGBTQ+ stuff everywhere. They even do a reconciliation Sunday service every year in June during pride month""",
]

# 4. Run the classification on the input string(s)
results = classifier(sentences)

# 5. Print the results
for i, result in enumerate(results):
    print(f"\nText: '{sentences[i]}'")
    print(f"Classification Results:")
    # Results can be a list of dictionaries if top_k is used
    if isinstance(result, list):
        for label_info in result:
            print(f"- Label: {label_info['label']}, Score: {label_info['score']:.4f}")
    else:
        print(f"- Label: {result['label']}, Score: {result['score']:.4f}")

Text: 'St. John's Episcopal is a really beautiful community that preaches "faith in action" -- they welcome and assist migrants, partner with community organizations, run a housing first apartment building for unhoused folks, and they are part of the Together Colorado coalition of faith-based organizations that lobbies for anti-poverty legislation. Bonus: the cathedral is gorgeous and historic.'
Classification Results:
- Label: Christianity, Score: 0.8822

Text: 'I’m atheist but rehearse in a community choir at Christ Church United Methodist and they have pro LGBTQ+ stuff everywhere. They even do a reconciliation Sunday service every year in June during pride month'
Classification Results:
- Label: Christianity, Score: 0.9899