Instructions to use StormZJ/test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StormZJ/test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="StormZJ/test1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("StormZJ/test1") model = AutoModelForMaskedLM.from_pretrained("StormZJ/test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from StormZJ/test1: direct link, hf CLI and curl.
- Browser
- Download file 1.25 kB
-
https://huggingface.co/StormZJ/test1/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://StormZJ/test1@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/StormZJ/test1/resolve/refs%2Fpr%2F1/training_args.bin
1.25 kB
- Xet hash:
- f2ab5f7a39b3adcb82120e006fdc7649e51a4aa9aacfd47df5a78036ac926c28
- Size of remote file:
- 1.25 kB
- SHA256:
- 0112a73cccd1cbca77f15175ab6e5faa20a7294f2630917864b5f6ec4716b0d3
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