Instructions to use KalaiselvanD/mega_08_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/mega_08_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/mega_08_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/mega_08_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KalaiselvanD/mega_08_1: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/KalaiselvanD/mega_08_1/resolve/main/training_args.bin
- Command line
-
hf download hf://KalaiselvanD/mega_08_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KalaiselvanD/mega_08_1/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 889f28d60eda094cb5f76f77d7411715ad1a6dfaeea0802f7661b52e977b9dcf
- Size of remote file:
- 4.92 kB
- SHA256:
- 8b0c1b8ea1aed2c8b4bdfeab9be5402a8b10d73d25de0b425890dcab696fb4ff
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