Instructions to use NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Saving weights and logs of step 380000
Browse files
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