Instructions to use TheJournal/model_demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheJournal/model_demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TheJournal/model_demo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TheJournal/model_demo") model = AutoModelForSequenceClassification.from_pretrained("TheJournal/model_demo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TheJournal/model_demo: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/TheJournal/model_demo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TheJournal/model_demo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TheJournal/model_demo/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- d61c531ec78ee173af4daf4d99a870dccacb1c09da8bf34d2e43146e094f4995
- Size of remote file:
- 438 MB
- SHA256:
- 2034399240ec83ed44baa5594a856d63ff5dcd54aa8f38c809538c6f7a0c13b1
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