Instructions to use KBLab/megatron.bert-base.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-base.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-base.wordpiece-64k-pretok.25k-steps")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KBLab/megatron.bert-base.wordpiece-64k-pretok.25k-steps") model = AutoModel.from_pretrained("KBLab/megatron.bert-base.wordpiece-64k-pretok.25k-steps") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b0c8cac3d3bac88882f9a75f8e60d597f0bee0c329572525d23a52f2ca7c816
- Size of remote file:
- 541 MB
- SHA256:
- 35a0e078278c3a7f70f1d6445efe53bb33ec15b4ed2230c525d794fc768609c2
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