Instructions to use surajp/SanBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use surajp/SanBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="surajp/SanBERTa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("surajp/SanBERTa") model = AutoModelForMaskedLM.from_pretrained("surajp/SanBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from surajp/SanBERTa: direct link, hf CLI and curl.
- Browser
- Download file 237 Bytes
-
https://huggingface.co/surajp/SanBERTa/resolve/refs%2Fpr%2F1/tokenizer_config.json
- Command line
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hf download hf://surajp/SanBERTa@refs/pr/1/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/surajp/SanBERTa/resolve/refs%2Fpr%2F1/tokenizer_config.json
237 Bytes
| {"max_len": 512, "model_type": "roberta", "do_lower_case": false, "keep_accents": true, "bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>"} |