Instructions to use beloiual/model_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beloiual/model_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="beloiual/model_3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("beloiual/model_3") model = AutoModelForMaskedLM.from_pretrained("beloiual/model_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45162d11e453bf1562c4f1a125771cd36dfbdfe0146dd4039bd13faff1f379df
- Size of remote file:
- 4.92 kB
- SHA256:
- b6e3d7dfdaff248b95ae025eee8c05628008f96a9e4454f129886ed64ac01773
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