Instructions to use ottersome/chkpnts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ottersome/chkpnts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ottersome/chkpnts")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ottersome/chkpnts") model = AutoModelForSequenceClassification.from_pretrained("ottersome/chkpnts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ottersome/chkpnts: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/ottersome/chkpnts/resolve/main/training_args.bin
- Command line
-
hf download hf://ottersome/chkpnts/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ottersome/chkpnts/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- 37615181a705ccb076c22bbd3b764a1b42c9841b4f1db90b7f442a04fbe1c399
- Size of remote file:
- 3.9 kB
- SHA256:
- 08ff368b24183d6bc658f732f1adc831222e2735af52ea87cafbdf18b2d22857
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