Instructions to use Extrabass/checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Extrabass/checkpoint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Extrabass/checkpoint")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Extrabass/checkpoint") model = AutoModelForSequenceClassification.from_pretrained("Extrabass/checkpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Extrabass/checkpoint: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/Extrabass/checkpoint/resolve/main/training_args.bin
- Command line
-
hf download hf://Extrabass/checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Extrabass/checkpoint/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 2149136a8f5d1b2596019cfc09cab3a690988c9e9622f37d2338e73624aa05de
- Size of remote file:
- 4.66 kB
- SHA256:
- 1ded25728dc095bd707bfff5a867f59af80be2822636311bb195072bc3fb05a2
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