Text Classification
Transformers
PyTorch
Safetensors
bert
voicemail-detection
text-embeddings-inference
Instructions to use Adya662/bert-tiny-amd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adya662/bert-tiny-amd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Adya662/bert-tiny-amd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Adya662/bert-tiny-amd") model = AutoModelForSequenceClassification.from_pretrained("Adya662/bert-tiny-amd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 125 Bytes
46b5225 | 1 2 3 4 5 6 7 8 | {
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"unk_token": "[UNK]"
}
|