Instructions to use JJ-Tae/Pretraining_Test_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JJ-Tae/Pretraining_Test_v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JJ-Tae/Pretraining_Test_v5")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("JJ-Tae/Pretraining_Test_v5") model = AutoModelForMaskedLM.from_pretrained("JJ-Tae/Pretraining_Test_v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b5d07a5112c5246ff3550e909735c137c9352815bf1180c7abed404bb881ce0
- Size of remote file:
- 4.92 kB
- SHA256:
- dae5543e60db95352e044f9116daad2128df40e5a9ff0d3dc922095f48b1d9d0
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