Instructions to use marlex7/successiveKD-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marlex7/successiveKD-Mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marlex7/successiveKD-Mini")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marlex7/successiveKD-Mini") model = AutoModelForSequenceClassification.from_pretrained("marlex7/successiveKD-Mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from marlex7/successiveKD-Mini: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/marlex7/successiveKD-Mini/resolve/main/training_args.bin
- Command line
-
hf download hf://marlex7/successiveKD-Mini/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/marlex7/successiveKD-Mini/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 6c52cab0e6b56ce10ac9eb4d10475ab1089fa10c5290187b59a0a8671c30d217
- Size of remote file:
- 4.73 kB
- SHA256:
- 42c20ecf567afcedb7adada16e2bcc89892a13cf0920a206c9cb6d8790af4bb7
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