Instructions to use Harini2506/second_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Harini2506/second_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Harini2506/second_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Harini2506/second_model") model = AutoModelForTokenClassification.from_pretrained("Harini2506/second_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Harini2506/second_model: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Harini2506/second_model/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Harini2506/second_model@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Harini2506/second_model/resolve/refs%2Fpr%2F1/training_args.bin
4.54 kB
- Xet hash:
- 5a7b55b0436b3f6b6ffd15dadced71c1483fc4fa55b4c72516bf6c3513b78942
- Size of remote file:
- 4.54 kB
- SHA256:
- 328271c11d49a77099f7bb79d3d7ef37e8757d3f61b705b17e39179e2f778445
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