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:
- dad5c368a03bfcaa2afc55365f5591f62b8cc22c3ef0c018f10339d85ec5c2dc
- Size of remote file:
- 3.44 kB
- SHA256:
- 60c8857d71a1f7f53bf57cfa11ea6c964ddb1ecdaf431ff724cbcc94b9676d2b
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