Instructions to use ksmcg/push_hub_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ksmcg/push_hub_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ksmcg/push_hub_test")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ksmcg/push_hub_test") model = AutoModelForMaskedLM.from_pretrained("ksmcg/push_hub_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82a532c279f40dc7087333903c96b35fa5ab93f6daa1fd389fa06240cc33ca75
- Size of remote file:
- 438 MB
- SHA256:
- a0c70bd099c73f17ce929da47d2871efe3787b3c4a62ca8c234f3f0d3544ce83
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