Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth") model = AutoModelForMaskedLM.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth/resolve/main/flax_model.msgpack
436 MB
- Xet hash:
- c3edc4e409452cc58ca447513cf43b52abda4212c1e2da0725c9285b4a76a70a
- Size of remote file:
- 436 MB
- SHA256:
- 32edfaa7e6db78b1907c7b69062dd56e414c8d2f5a4ed22632a3354893b9b567
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