Instructions to use roscoyoon/bert-base-uncased-issues-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roscoyoon/bert-base-uncased-issues-128 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="roscoyoon/bert-base-uncased-issues-128")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("roscoyoon/bert-base-uncased-issues-128") model = AutoModelForMaskedLM.from_pretrained("roscoyoon/bert-base-uncased-issues-128", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2074e1e8e1934a5e1b326636c39ecdbd4ecb138f3600bdc7de5d61d363df3e6e
- Size of remote file:
- 3.25 kB
- SHA256:
- 2f336f07b878cb3895d00f0a1e5ce16b524e0978592deea607a33de25488770c
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