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:
- ccabcf0ffbab8e914a58025bdbe6ff0e0bdbed8dd9886bb259432f51cbc0093e
- Size of remote file:
- 501 MB
- SHA256:
- 92bbea56fd9d57b3aa1e65b9f68ca94122897f837290789708b8789e847a3c08
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