Instructions to use KBLab/megatron.bert-base.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-base.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-base.unigram-64k-pretok.25k-steps")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KBLab/megatron.bert-base.unigram-64k-pretok.25k-steps") model = AutoModel.from_pretrained("KBLab/megatron.bert-base.unigram-64k-pretok.25k-steps") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6bf877f2d93e9a09cd86eeb1dce78e9c3e8f4e8e922c918e589e86ee3cdb61f
- Size of remote file:
- 541 MB
- SHA256:
- dbe5a987d84d6e42d4af1339ff2e376ddd8610249f78cbf89c9b309e97d09832
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