Instructions to use google/bert_for_seq_generation_L-24_bbc_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/bert_for_seq_generation_L-24_bbc_encoder with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("google/bert_for_seq_generation_L-24_bbc_encoder") model = AutoModel.from_pretrained("google/bert_for_seq_generation_L-24_bbc_encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from google/bert_for_seq_generation_L-24_bbc_encoder: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://google/bert_for_seq_generation_L-24_bbc_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 02f6eb65a73daa2a4fb2d2dcdd4c119af4aa50cd6e8b90939682930231cd85d8
- Size of remote file:
- 1.42 GB
- SHA256:
- a339333498006a287c8a5808e8f3f2e59fc55d1c922cfcab781c230e47ea9ca8
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