Instructions to use ncardus/TrainedMLMBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ncardus/TrainedMLMBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ncardus/TrainedMLMBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ncardus/TrainedMLMBERT") model = AutoModel.from_pretrained("ncardus/TrainedMLMBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
- pytorch_model.bin +2 -2
config.json
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"transformers_version": "4.31.0",
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"type_vocab_size": 1,
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"use_cache": true,
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}
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"transformers_version": "4.31.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 4000
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:8215a8eece4f5092d11762647f8dd76c442a1de45e4f506c4dc49076d0cd35a0
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size 357300945
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