Instructions to use ncardus/TrainedMLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ncardus/TrainedMLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ncardus/TrainedMLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ncardus/TrainedMLM") model = AutoModelForMaskedLM.from_pretrained("ncardus/TrainedMLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ncardus/TrainedMLM: direct link, hf CLI and curl.
- Browser
- Download file 360 MB
-
https://huggingface.co/ncardus/TrainedMLM/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://ncardus/TrainedMLM@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ncardus/TrainedMLM/resolve/refs%2Fpr%2F1/pytorch_model.bin
360 MB
- Xet hash:
- c4bdb413473ad1d7e4aaac4a678f06afe2cd57e62479c99d3087aed103d39602
- Size of remote file:
- 360 MB
- SHA256:
- cd2f06eb1f0e4a89c4473767a6a84192480dc7e7d02a2fc728f830f2b6be2ef8
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