Instructions to use msharma95/hml-best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msharma95/hml-best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="msharma95/hml-best")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("msharma95/hml-best") model = AutoModelForMaskedLM.from_pretrained("msharma95/hml-best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c35283e0185dcdbef7d047bad6171d2ac367d1d2815351f48165362a6fb3651
- Size of remote file:
- 34.2 MB
- SHA256:
- ce1ca11e04914bba2e1e4ddc72fe06e43246bca15d916b0595b9258bfc5fb14b
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