Instructions to use Isuru0x01/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isuru0x01/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Isuru0x01/results")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Isuru0x01/results") model = AutoModelForMaskedLM.from_pretrained("Isuru0x01/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0341fd6e5f91fa12ef832317022bafe2706458284c6e201f5e2c90fae1df8ceb
- Size of remote file:
- 5.11 kB
- SHA256:
- d7dc6b32e27d07e0214b86c79a77ea96d8a7eb3e10496a1f0cc8c32f9ae2ebe6
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