Instructions to use hansgun/model_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hansgun/model_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hansgun/model_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hansgun/model_test") model = AutoModelForMaskedLM.from_pretrained("hansgun/model_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from hansgun/model_test: direct link, hf CLI and curl.
- Browser
- Download file 712 MB
-
https://huggingface.co/hansgun/model_test/resolve/main/tf_model.h5
- Command line
-
hf download hf://hansgun/model_test/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/hansgun/model_test/resolve/main/tf_model.h5
712 MB
- Xet hash:
- 6a4deac1a9af17a50f4b429088051d3501a3890d1b2f18f0b66b9b30dd8b26b3
- Size of remote file:
- 712 MB
- SHA256:
- 040c05cb8d5926189a93f58071dc99d90c01843dc7bc3d3b7a77686e8eb4d014
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