Instructions to use hangmu/9.4AIstudy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hangmu/9.4AIstudy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hangmu/9.4AIstudy")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hangmu/9.4AIstudy") model = AutoModelForMaskedLM.from_pretrained("hangmu/9.4AIstudy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hangmu/9.4AIstudy: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/hangmu/9.4AIstudy/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hangmu/9.4AIstudy/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hangmu/9.4AIstudy/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 071ee81b03b71cf1609675e52f7dbddf6f84adeb19a545325f87c3ed2a8cc5f6
- Size of remote file:
- 438 MB
- SHA256:
- 97ffe6f24c4fae398a0466ec856a56c10f8c0616e84bf492ab8508c1ddf33ecf
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