Instructions to use tner/roberta-large-mit-restaurant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/roberta-large-mit-restaurant with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/roberta-large-mit-restaurant")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/roberta-large-mit-restaurant") model = AutoModelForTokenClassification.from_pretrained("tner/roberta-large-mit-restaurant", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4fbc1476a1488cdcb86e4ecf4fdeec25957c0ae2293d98a781ed8ded224377b
- Size of remote file:
- 1.42 GB
- SHA256:
- 66cebade177378718e885f09d6adb3eb4b877a89adadfd22dd44a3a1ee941709
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