Instructions to use versae/roberta-base-ncc-512d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/roberta-base-ncc-512d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="versae/roberta-base-ncc-512d")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("versae/roberta-base-ncc-512d") model = AutoModelForMaskedLM.from_pretrained("versae/roberta-base-ncc-512d", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Saving weights and logs of step 484000
Browse files- events.out.tfevents.1643652616.t1v-n-00e295a4-w-0.190699.0.v2 +2 -2
- flax_model.msgpack +1 -1
- wandb/run-20220131_181009-hhypc7yn/files/output.log +2 -2
- wandb/run-20220131_181009-hhypc7yn/files/wandb-summary.json +1 -1
- wandb/run-20220131_181009-hhypc7yn/logs/debug-internal.log +2 -2
- wandb/run-20220131_181009-hhypc7yn/run-hhypc7yn.wandb +2 -2
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