Instructions to use KBLab/megatron.bert-base.unigram-32k-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-32k-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-32k-pretok.25k-steps")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KBLab/megatron.bert-base.unigram-32k-pretok.25k-steps") model = AutoModel.from_pretrained("KBLab/megatron.bert-base.unigram-32k-pretok.25k-steps") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 376ec7ac23658ec80e84ea3f4884a258482f6cdffce44dcbace0d310c136375c
- Size of remote file:
- 442 MB
- SHA256:
- ee2df0b46b744d461dd2f04b1520433912b88b18230f7fd61fca4c5da6600eb7
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