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")# 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") - Notebooks
- Google Colab
- Kaggle
Saving weights and logs of step 5000
Browse files
events.out.tfevents.1639912087.t1v-n-4e27a527-w-0.1954459.0.v2
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size 735136
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flax_model.msgpack
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size 498796983
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