Fill-Mask
Transformers
Safetensors
PyTorch
English
saute
feature-extraction
masked-language-modeling
dialogue
speaker-aware
transformer
custom_code
Instructions to use JustinDuc/saute with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JustinDuc/saute with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JustinDuc/saute", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JustinDuc/saute", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from JustinDuc/saute: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/JustinDuc/saute/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://JustinDuc/saute/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/JustinDuc/saute/resolve/main/last-checkpoint/optimizer.pt
246 MB
- Xet hash:
- 74193a5a4595978f7bbe9d27b7c90d200c2d60aaea2b7617aa367c627ecdcfa2
- Size of remote file:
- 246 MB
- SHA256:
- 8459e376ea931998d33c038080ed53ca14e8b5c5ec8f7e930035f963ea0160eb
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