Instructions to use tuhink/hacking-rewards-general-train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tuhink/hacking-rewards-general-train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tuhink/hacking-rewards-general-train")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tuhink/hacking-rewards-general-train") model = AutoModelForSequenceClassification.from_pretrained("tuhink/hacking-rewards-general-train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tuhink/hacking-rewards-general-train: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/tuhink/hacking-rewards-general-train/resolve/main/training_args.bin
- Command line
-
hf download hf://tuhink/hacking-rewards-general-train/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tuhink/hacking-rewards-general-train/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- c67896e4499946bf25344e12a7134fe8346a431ea158a1e13d91bc148a92546b
- Size of remote file:
- 5.37 kB
- SHA256:
- 82794db422e5e0d9ffa1a6871f656a013d925dbfc72704f454693cdc12e33686
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