Instructions to use soniakris/Sonia_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use soniakris/Sonia_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="soniakris/Sonia_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("soniakris/Sonia_model") model = AutoModelForMaskedLM.from_pretrained("soniakris/Sonia_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from soniakris/Sonia_model: direct link, hf CLI and curl.
- Browser
- Download file 174 Bytes
-
https://huggingface.co/soniakris/Sonia_model/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://soniakris/Sonia_model/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/soniakris/Sonia_model/resolve/main/tokenizer_config.json
174 Bytes
| {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "model_max_length": 512, "name_or_path": "bert-base-uncased"} |