Instructions to use smeoni/roberta-base-clrp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smeoni/roberta-base-clrp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="smeoni/roberta-base-clrp")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("smeoni/roberta-base-clrp") model = AutoModelForMaskedLM.from_pretrained("smeoni/roberta-base-clrp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc40926f0c24008d046f072121e808b2bcf7903a3aa9fc21ca97de6232c04db6
- Size of remote file:
- 499 MB
- SHA256:
- 3410c1d5a00a9d4d1195e5ff67fb99561609c03b548d3992e892d245af020e62
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