Instructions to use msharma95/hml-en-400 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msharma95/hml-en-400 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="msharma95/hml-en-400")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("msharma95/hml-en-400") model = AutoModelForMaskedLM.from_pretrained("msharma95/hml-en-400", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5022e1d191317c9c0fb04d0a1086f6e0bd5fe012c4030dcb2a3b82c987180931
- Size of remote file:
- 68.3 MB
- SHA256:
- f396362ca82772bda1d0cffa730eaae3cfcd3bdbd30633f6bbe0cc140bef9985
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