Instructions to use gus1999/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gus1999/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gus1999/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gus1999/model") model = AutoModelForMaskedLM.from_pretrained("gus1999/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gus1999/model: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/gus1999/model/resolve/main/training_args.bin
- Command line
-
hf download hf://gus1999/model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gus1999/model/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 6bb77f9751b631a85d3c80d5938494b54245a4fa4b46db04313a34b8483ee72c
- Size of remote file:
- 3.31 kB
- SHA256:
- 90155727f4b5ffe86b5b76225ec4418e22260f32e18fed7d56a6ca3574814455
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