Instructions to use moussaKam/barthez with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moussaKam/barthez with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="moussaKam/barthez")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("moussaKam/barthez") model = AutoModelForSeq2SeqLM.from_pretrained("moussaKam/barthez", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92cad2f68b0de46f927f654754246c5dc5d9360920abed56163ee76a0c5fedac
- Size of remote file:
- 711 MB
- SHA256:
- 72f066121e2ee6c83d109c8edb2b7c8b9cea53492a9eed1a8fbddb247f3a1ad0
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