Instructions to use LDD/bert_mlm_new2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LDD/bert_mlm_new2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LDD/bert_mlm_new2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LDD/bert_mlm_new2") model = AutoModel.from_pretrained("LDD/bert_mlm_new2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from LDD/bert_mlm_new2: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/LDD/bert_mlm_new2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://LDD/bert_mlm_new2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/LDD/bert_mlm_new2/resolve/main/pytorch_model.bin
409 MB
- Xet hash:
- b403988345b1a73452095e57312b8f55e78ecea14692395d9c94f3f36e72e6ce
- Size of remote file:
- 409 MB
- SHA256:
- 866bb5ae7a632ce7c4f4545a377fd105bd257d44324cd85501b419da6287d372
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