Instructions to use textattack/albert-base-v2-RTE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/albert-base-v2-RTE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/albert-base-v2-RTE")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/albert-base-v2-RTE") model = AutoModelForSequenceClassification.from_pretrained("textattack/albert-base-v2-RTE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from textattack/albert-base-v2-RTE: direct link, hf CLI and curl.
- Browser
- Download file 156 Bytes
-
https://huggingface.co/textattack/albert-base-v2-RTE/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://textattack/albert-base-v2-RTE/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/textattack/albert-base-v2-RTE/resolve/main/special_tokens_map.json
156 Bytes
| {"bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "<unk>", "sep_token": "[SEP]", "pad_token": "<pad>", "cls_token": "[CLS]", "mask_token": "[MASK]"} |