Instructions to use Anshul017/nli_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anshul017/nli_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Anshul017/nli_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Anshul017/nli_model") model = AutoModelForSequenceClassification.from_pretrained("Anshul017/nli_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Anshul017/nli_model: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/Anshul017/nli_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Anshul017/nli_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Anshul017/nli_model/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- 8cdb58cee2ec58f685b53ee6588f0834ac0b67a42ccfaf97cb803192d6f90e3a
- Size of remote file:
- 5.2 kB
- SHA256:
- 62f84cfc19cb2d3c96ae350d2b4dcdd81203ab59d92dffbef8874a616afbaeda
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