Instructions to use ChillingDream/dap-xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChillingDream/dap-xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ChillingDream/dap-xlm-roberta-base")# Load model directly from transformers import AutoTokenizer, RobertaForRLM tokenizer = AutoTokenizer.from_pretrained("ChillingDream/dap-xlm-roberta-base") model = RobertaForRLM.from_pretrained("ChillingDream/dap-xlm-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b467eec776cc2fb0024ac8d78e4cac5e945ccd740dc41d5b41da083815768cb1
- Size of remote file:
- 1.11 GB
- SHA256:
- 76d07706dc01eac1050da457ac32855adc0548b0b113a6632091dc228e2478bf
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