Instructions to use KalaiselvanD/output_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/output_new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/output_new")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/output_new") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/output_new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KalaiselvanD/output_new: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/KalaiselvanD/output_new/resolve/main/training_args.bin
- Command line
-
hf download hf://KalaiselvanD/output_new/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KalaiselvanD/output_new/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 768cca80729ee8f22cc01bf8cbbcae6bad209aa831cd299367670d5e9e5890aa
- Size of remote file:
- 4.92 kB
- SHA256:
- 25294a73666c0bc0919d147a5b4b772d04959d4e39d86647f7cc1b74a21ad4da
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