Instructions to use msharma95/hml-es-best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msharma95/hml-es-best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="msharma95/hml-es-best")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("msharma95/hml-es-best") model = AutoModelForMaskedLM.from_pretrained("msharma95/hml-es-best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26dd4974fd8191f6d352e4ba75e981e2663d2b9807a1633c66c77084d9ca97d0
- Size of remote file:
- 68.3 MB
- SHA256:
- b93427b883ca6b277fbdf41e40568643655c2179e463114b84021f6122527a57
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