Instructions to use lgrobol/xlm-r-CreoleEval_kon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgrobol/xlm-r-CreoleEval_kon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lgrobol/xlm-r-CreoleEval_kon")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lgrobol/xlm-r-CreoleEval_kon") model = AutoModelForMaskedLM.from_pretrained("lgrobol/xlm-r-CreoleEval_kon") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2a4198e62e88fa91c476b41f3f3d9c3818b2644632bfedb7a5fdbff9c458149
- Size of remote file:
- 1.11 GB
- SHA256:
- 5e67b2b8b4b16e2a8aa7fbc6578626dbcf63acb813e74aa0cce4fce59d233ee5
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