Instructions to use Rocketknight1/test_callback_upload with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rocketknight1/test_callback_upload with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rocketknight1/test_callback_upload")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rocketknight1/test_callback_upload") model = AutoModelForSequenceClassification.from_pretrained("Rocketknight1/test_callback_upload", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from Rocketknight1/test_callback_upload: direct link, hf CLI and curl.
- Browser
- Download file 434 MB
-
https://huggingface.co/Rocketknight1/test_callback_upload/resolve/main/tf_model.h5
- Command line
-
hf download hf://Rocketknight1/test_callback_upload/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/Rocketknight1/test_callback_upload/resolve/main/tf_model.h5
434 MB
- Xet hash:
- ea6d6e72d7203438f0ca065271d8f02f9fc5eebbe4199bcbfad361b8956fee50
- Size of remote file:
- 434 MB
- SHA256:
- 6625dfc2281262e95ba8dca78ebd29360a6861f6e5a850bd1408042d88a7c973
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