Instructions to use vppvgit/Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vppvgit/Finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vppvgit/Finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vppvgit/Finetuned") model = AutoModelForMaskedLM.from_pretrained("vppvgit/Finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26a371d9f45650d328fcd5e7269d508d60db6ab970b323a6c4fe7389408d4912
- Size of remote file:
- 443 MB
- SHA256:
- ef3dfea5d7a7e27ffb9bbb7aa305b55f5cd6b551188aa49f636c73f46e371d52
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