Text Classification
Transformers
Safetensors
English
bert
sentiment analysis
text classification
news
reviews
text-embeddings-inference
Instructions to use mervp/SentimentBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mervp/SentimentBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mervp/SentimentBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mervp/SentimentBERT") model = AutoModelForSequenceClassification.from_pretrained("mervp/SentimentBERT") - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |