Instructions to use KalaiselvanD/distilbert_07_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/distilbert_07_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/distilbert_07_3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/distilbert_07_3") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/distilbert_07_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KalaiselvanD/distilbert_07_3: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/KalaiselvanD/distilbert_07_3/resolve/main/training_args.bin
- Command line
-
hf download hf://KalaiselvanD/distilbert_07_3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KalaiselvanD/distilbert_07_3/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- e54ffec5af8d3a6f8d6772a7ea4977a9b36dec1eac3506099b8997dd174c6fda
- Size of remote file:
- 4.92 kB
- SHA256:
- a4b74017f9345a36affbcafe3672986aa4c7687e82b07dcdf9b9bcc25e00f4e6
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