Instructions to use mahdiyar/snli-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahdiyar/snli-6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mahdiyar/snli-6")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mahdiyar/snli-6") model = AutoModelForMaskedLM.from_pretrained("mahdiyar/snli-6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b642717d3f86eac7fe0fbf6ba6053f84673cdd2233e51a27fdd95c1f2b59cb92
- Size of remote file:
- 1.4 kB
- SHA256:
- 9430721407d7551cde0a61c3f1de1643360ea0a3eae2742888f7b5668fdc397d
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