Text Classification
Transformers
Safetensors
PyTorch
bert
sentiment-analysis
sst2
glue
text-embeddings-inference
Instructions to use mi55th/bert-sst2-nesterov with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mi55th/bert-sst2-nesterov with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mi55th/bert-sst2-nesterov")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mi55th/bert-sst2-nesterov") model = AutoModelForSequenceClassification.from_pretrained("mi55th/bert-sst2-nesterov", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 125 Bytes
43c600e | 1 2 3 4 5 6 7 8 | {
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"unk_token": "[UNK]"
}
|