Instructions to use LDD/bert_mlm_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LDD/bert_mlm_new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LDD/bert_mlm_new")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LDD/bert_mlm_new") model = AutoModel.from_pretrained("LDD/bert_mlm_new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from LDD/bert_mlm_new: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/LDD/bert_mlm_new/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://LDD/bert_mlm_new/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/LDD/bert_mlm_new/resolve/main/pytorch_model.bin
409 MB
- Xet hash:
- 96f01df01739dc90cb8e0078ef9b66de3eab2a6df6bbbba75454866da9a36f55
- Size of remote file:
- 409 MB
- SHA256:
- 1301347dfe407603853004cf68c0f2b39b9154f660b4bb973cd8139c10ad7a8c
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