Instructions to use KBLab/megatron.bert-large.wordpiece-64k-pretok.25k-steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBLab/megatron.bert-large.wordpiece-64k-pretok.25k-steps with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="KBLab/megatron.bert-large.wordpiece-64k-pretok.25k-steps")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KBLab/megatron.bert-large.wordpiece-64k-pretok.25k-steps") model = AutoModel.from_pretrained("KBLab/megatron.bert-large.wordpiece-64k-pretok.25k-steps") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08d2abdcb9f9a2c88bae995f0bc4162d19415a94c911673cc5a54dafff1f0591
- Size of remote file:
- 1.48 GB
- SHA256:
- a4a2a0119bd75ad335e9e77ebcaae65fd4751c923b34091719b0c0cf9144b1ab
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