Instructions to use yzhou992/test_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yzhou992/test_model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="yzhou992/test_model2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("yzhou992/test_model2") model = AutoModelForMaskedLM.from_pretrained("yzhou992/test_model2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from yzhou992/test_model2: direct link, hf CLI and curl.
- Browser
- Download file 14.5 kB
-
https://huggingface.co/yzhou992/test_model2/resolve/main/rng_state.pth
- Command line
-
hf download hf://yzhou992/test_model2/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/yzhou992/test_model2/resolve/main/rng_state.pth
14.5 kB
- Xet hash:
- 6acae2cd7993691d32645d5567c0978676c2103e0f1ba4fa50cd6367208541a0
- Size of remote file:
- 14.5 kB
- SHA256:
- b832123d3d9c2ea9eb61c4527d9c976a4fa92cce39004daca2e044db445aa20b
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