Instructions to use AnReu/albert-for-math-ar-base-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnReu/albert-for-math-ar-base-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnReu/albert-for-math-ar-base-ft")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnReu/albert-for-math-ar-base-ft") model = AutoModelForSequenceClassification.from_pretrained("AnReu/albert-for-math-ar-base-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from AnReu/albert-for-math-ar-base-ft: direct link, hf CLI and curl.
- Browser
- Download file 244 Bytes
-
https://huggingface.co/AnReu/albert-for-math-ar-base-ft/resolve/main/special_tokens_map.json
- Command line
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hf download hf://AnReu/albert-for-math-ar-base-ft/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/AnReu/albert-for-math-ar-base-ft/resolve/main/special_tokens_map.json
244 Bytes
| {"bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "<unk>", "sep_token": "[SEP]", "pad_token": "<pad>", "cls_token": "[CLS]", "mask_token": {"content": "[MASK]", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true}} |