Instructions to use junzai/ai12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junzai/ai12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="junzai/ai12")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("junzai/ai12") model = AutoModelForMaskedLM.from_pretrained("junzai/ai12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from junzai/ai12: direct link, hf CLI and curl.
- Browser
- Download file 1.21 kB
-
https://huggingface.co/junzai/ai12/resolve/main/training_args.bin
- Command line
-
hf download hf://junzai/ai12/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/junzai/ai12/resolve/main/training_args.bin
1.21 kB
- Xet hash:
- 00c8b74e44b807e2638828fb3591e594959052bde28966d99a4beb0aba2b8192
- Size of remote file:
- 1.21 kB
- SHA256:
- 7cdf577b6d35f2627ad38cc849be33581812693fcd2d0d4f6a44d7a6c2ac9422
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