Instructions to use g8a9/roberta-tiny-2l-10M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use g8a9/roberta-tiny-2l-10M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="g8a9/roberta-tiny-2l-10M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("g8a9/roberta-tiny-2l-10M") model = AutoModelForMaskedLM.from_pretrained("g8a9/roberta-tiny-2l-10M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f0de4e52c473825a6c282044edd933763ececd0c8dee7e99504d2dca0c33c67
- Size of remote file:
- 296 MB
- SHA256:
- 821125dcd05c4bcefa7293c37b6e69e758acd6e9b18b0bc0896a92b9bcaa4ae2
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