Instructions to use KalaiselvanD/funnel_08_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/funnel_08_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/funnel_08_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/funnel_08_1") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/funnel_08_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KalaiselvanD/funnel_08_1: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/KalaiselvanD/funnel_08_1/resolve/main/training_args.bin
- Command line
-
hf download hf://KalaiselvanD/funnel_08_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KalaiselvanD/funnel_08_1/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- e0ab462b926e64ce81d43df29b6c5f19881a907c5a2ad10db7ba0f46f6cc6da7
- Size of remote file:
- 4.92 kB
- SHA256:
- 7154052b5b1c1eb6bfa211601b889becbb4679b87e5460cbe7a6c3fa544e5ab4
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