Instructions to use KBLab/megatron.bert-large.wordpiece-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-large.wordpiece-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-large.wordpiece-32k-pretok.25k-steps")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KBLab/megatron.bert-large.wordpiece-32k-pretok.25k-steps") model = AutoModel.from_pretrained("KBLab/megatron.bert-large.wordpiece-32k-pretok.25k-steps") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6bf9c6a5d46b48f31bf75b026df6f521817665e4fc009a90fd1e3b7d3e2be31
- Size of remote file:
- 1.35 GB
- SHA256:
- debebfd8e4cd8e64632b84477f39ae1ed66f89dd77939494638274b855a30321
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