Instructions to use Harini2506/first_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Harini2506/first_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Harini2506/first_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Harini2506/first_model") model = AutoModelForTokenClassification.from_pretrained("Harini2506/first_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Harini2506/first_model: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Harini2506/first_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Harini2506/first_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Harini2506/first_model/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 9975b48859b8891a73adea2423ebf29b8f2025de51d24185b047f8fb89013a49
- Size of remote file:
- 4.54 kB
- SHA256:
- 9e9c0831c4d9b56a7c93ac0a29b58301e7ffaa07fdf845a4474106f4c8855eb7
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