Instructions to use simecek/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simecek/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simecek/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simecek/results") model = AutoModelForMaskedLM.from_pretrained("simecek/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from simecek/results: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/simecek/results/resolve/main/training_args.bin
- Command line
-
hf download hf://simecek/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/simecek/results/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- dfac0f1b4b33e805cdb3a5e6dcf54296d26ec2b3c94b49a2b9dc3077869fbc05
- Size of remote file:
- 5.18 kB
- SHA256:
- d39cc9a0185d8f11d3d0091f65d2411dad52150660aa6a47c27c37ea72d68593
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