Instructions to use KBLab/megatron.bert-base.spe-bpe-64k-no_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.spe-bpe-64k-no_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.spe-bpe-64k-no_pretok.25k-steps")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KBLab/megatron.bert-base.spe-bpe-64k-no_pretok.25k-steps") model = AutoModel.from_pretrained("KBLab/megatron.bert-base.spe-bpe-64k-no_pretok.25k-steps") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c0938ade2d8b00cf89089a8338c5a56cc278e2ea72264f8091ba31d65e30251
- Size of remote file:
- 541 MB
- SHA256:
- fc46531c831dad124d434b9182ea7aea46973137063271bd6585fb61729228f0
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