Instructions to use qdenisq/BertFormalityClassificiation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qdenisq/BertFormalityClassificiation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="qdenisq/BertFormalityClassificiation")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("qdenisq/BertFormalityClassificiation") model = AutoModelForMaskedLM.from_pretrained("qdenisq/BertFormalityClassificiation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from qdenisq/BertFormalityClassificiation: direct link, hf CLI and curl.
- Browser
- Download file 28 Bytes
-
https://huggingface.co/qdenisq/BertFormalityClassificiation/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://qdenisq/BertFormalityClassificiation/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/qdenisq/BertFormalityClassificiation/resolve/main/tokenizer_config.json
28 Bytes
| { | |
| "model_type": "bert" | |
| } |