Instructions to use antoinelouis/netbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use antoinelouis/netbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="antoinelouis/netbert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("antoinelouis/netbert") model = AutoModelForMaskedLM.from_pretrained("antoinelouis/netbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from antoinelouis/netbert: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/antoinelouis/netbert/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://antoinelouis/netbert/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/antoinelouis/netbert/resolve/main/flax_model.msgpack
433 MB
- Xet hash:
- de9def5767bd2fefcaafd32e11aad95c5e7f84efc8d731acfd3f52d63b100c20
- Size of remote file:
- 433 MB
- SHA256:
- aa1e47a7bddd927d8c2a0147693fa2eabc7e03e38c003c2b658788467962decf
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