Instructions to use KBLab/megatron.bert-large.unigram-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.unigram-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.unigram-64k-pretok.25k-steps")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KBLab/megatron.bert-large.unigram-64k-pretok.25k-steps") model = AutoModel.from_pretrained("KBLab/megatron.bert-large.unigram-64k-pretok.25k-steps") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcd1b2740d8688bf43380b85b38a439e1f3c4971a7501964946049605141b38e
- Size of remote file:
- 1.48 GB
- SHA256:
- d47505c7ee5b2a7c374b9d991d786a3a1f88728c28cf8b8b6ea26e4cc7cf9cdf
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