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 training_args.bin from celential/erc: direct link, hf CLI and curl.
- Browser
- Download file 1.24 kB
-
https://huggingface.co/celential/erc/resolve/main/training_args.bin
- Command line
-
hf download hf://celential/erc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/celential/erc/resolve/main/training_args.bin
1.24 kB
- Xet hash:
- f51fc628529d35c04ffd18987d8c7cbac68f2e336dc27a294be0cde0eec2f9d9
- Size of remote file:
- 1.24 kB
- SHA256:
- f066847cba3588229ec48f320187e3452b7f13c68e671fa999000e7f30af89ba
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