Instructions to use stolenpyjak/testing_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stolenpyjak/testing_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="stolenpyjak/testing_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("stolenpyjak/testing_model") model = AutoModelForMaskedLM.from_pretrained("stolenpyjak/testing_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fcd6e8b0705ace30f45d2318598a9c94eab4e5fb943bf0f395402b91cee86993
- Size of remote file:
- 329 MB
- SHA256:
- bf20a78ec2dad5508e0289527dc3f9926bff125a6b2f1062c888dd3e2f50cb58
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