Instructions to use Harini2506/first_model_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Harini2506/first_model_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Harini2506/first_model_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Harini2506/first_model_1") model = AutoModelForTokenClassification.from_pretrained("Harini2506/first_model_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Harini2506/first_model_1: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Harini2506/first_model_1/resolve/main/training_args.bin
- Command line
-
hf download hf://Harini2506/first_model_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Harini2506/first_model_1/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 884eba13f49769fb7124f45d183a9fbb728f8196576fd13ce2425eec41f5247b
- Size of remote file:
- 4.54 kB
- SHA256:
- c6e784740561e2b4b7665649cb4b9e0ce7f0153e86956784361ba9dccca88a3e
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