Instructions to use gijs/aces-roberta-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gijs/aces-roberta-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="gijs/aces-roberta-10")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("gijs/aces-roberta-10") model = AutoModelForTokenClassification.from_pretrained("gijs/aces-roberta-10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b845744360d59f2f2480d63e1bc9a657fdcc975b81496faa1cc6b7b7515ca4b8
- Size of remote file:
- 1.42 GB
- SHA256:
- 13aadeaa0e871643b52aa7d70539a570f77fc847922a24f339e9d3ba438e5e45
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