Instructions to use jerteh/Jerteh-355 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jerteh/Jerteh-355 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jerteh/Jerteh-355")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jerteh/Jerteh-355") model = AutoModelForMaskedLM.from_pretrained("jerteh/Jerteh-355") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8763aa5f30364a15dfa9853838fa94fb7a0c9c646a173ec36dbde4f043998856
- Size of remote file:
- 1.42 GB
- SHA256:
- 392e5a97841fd385b9ddac80abc640fe0b7bbc78ffaebf7c9e5db1e40ae43b8f
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