Instructions to use hardikpatel/debertabasepiitrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hardikpatel/debertabasepiitrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hardikpatel/debertabasepiitrained")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hardikpatel/debertabasepiitrained") model = AutoModelForTokenClassification.from_pretrained("hardikpatel/debertabasepiitrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hardikpatel/debertabasepiitrained: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/hardikpatel/debertabasepiitrained/resolve/main/tokenizer.json
- Command line
-
hf download hf://hardikpatel/debertabasepiitrained/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hardikpatel/debertabasepiitrained/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.