Instructions to use celential/erc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use celential/erc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="celential/erc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("celential/erc") model = AutoModelForSequenceClassification.from_pretrained("celential/erc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from celential/erc: direct link, hf CLI and curl.
- Browser
- Download file 760 kB
-
https://huggingface.co/celential/erc/resolve/main/spiece.model
- Command line
-
hf download hf://celential/erc/spiece.model
-
curl -L -o spiece.model https://huggingface.co/celential/erc/resolve/main/spiece.model
760 kB
This file contains binary data. It cannot be displayed, but you can still download it.