Instructions to use ujgeie/bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ujgeie/bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ujgeie/bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ujgeie/bert") model = AutoModelForMaskedLM.from_pretrained("ujgeie/bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 155000
Browse files- config.json +1 -1
- model.safetensors +1 -1
- training_args.bin +1 -1
config.json
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"_name_or_path": "bert/checkpoint-
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"architectures": [
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"BertForMaskedLM"
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"_name_or_path": "bert/checkpoint-150000",
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"BertForMaskedLM"
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model.safetensors
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training_args.bin
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