Instructions to use maple/roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maple/roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="maple/roberta-large")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("maple/roberta-large") model = AutoModelForTokenClassification.from_pretrained("maple/roberta-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0922785f3b3778e495a53e8f07fd2cff7b8ee51142f1362e3e8dc64a90c73fb
- Size of remote file:
- 1.42 GB
- SHA256:
- 167e38936dbcc99f01478c0e6dcbdf18bb5811ee4ca4cf801abb4b375a4ea4ca
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