# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("alanwang2001/BERT-sentiment-lora")
model = AutoModelForSequenceClassification.from_pretrained("alanwang2001/BERT-sentiment-lora")Quick Links
BERT-sentiment-lora
This model is a fine-tuned version of google-bert/bert-base-uncased for 3-class movie review sentiment classification.
Labels
0→ negative (−1)1→ mixed (0)2→ positive (+1)
Training details
- Architecture: BertForSequenceClassification
- Hidden size: 768, Layers: 12, Heads: 12
- Framework: Transformers 5.3.0
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Model tree for alanwang2001/BERT-sentiment-lora
Base model
google-bert/bert-base-uncased
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alanwang2001/BERT-sentiment-lora")