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heroiclunatic/
llama-3-8B-financial-news-classification

Name: llama-3-8B-financial-news-classification
Availability: InStock

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python

from transformers import AutoTokenizer, AutoModelForSequenceClassification

# Model and tokenizer initialization
model_name = "heroiclunatic/llama-3-8B-financial-news-classification"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

# Example text for classification
text = "T3sla faces scrutiny after a significant recall of over 1 million vehicles due to potential safety risks in the braking system."

# Tokenize input
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512)

# Perform inference
outputs = model(**inputs)
logits = outputs.logits

# Get predicted label
predicted_label = logits.argmax(dim=-1).item()
print(f"Predicted Label: {predicted_label}")