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Example:
from transformers import AutoTokenizer, AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("burakutf/finetuned-finbert-crypto")
tokenizer = AutoTokenizer.from_pretrained("yiyanghkust/finbert-tone")
text = "Golden Crosses Signal Breakout Potential for Bitcoin and Altcoins"
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=128)
outputs = model(**inputs)
pred = outputs.logits.argmax(dim=1).item()
label_map = {0: "negative", 1: "neutral", 2: "positive"}
print("Response:", label_map[pred]) -
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