Instructions to use pvl/labse_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pvl/labse_bert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("pvl/labse_bert") model = AutoModelForPreTraining.from_pretrained("pvl/labse_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from pvl/labse_bert: direct link, hf CLI and curl.
- Browser
- Download file 1.89 GB
-
https://huggingface.co/pvl/labse_bert/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://pvl/labse_bert/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/pvl/labse_bert/resolve/main/flax_model.msgpack
1.89 GB
- Xet hash:
- e2d1dd46ba98cbc0a0c6e13c3984d088d80e0466b837acaea413788c6a9bc3e1
- Size of remote file:
- 1.89 GB
- SHA256:
- b893b5997ed8ea1b2df52f0e3bb1e2b3af1b6e6bfd5bf620142b3bb06f830520
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