Instructions to use KalaiselvanD/fine_tuned_model_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/fine_tuned_model_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/fine_tuned_model_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/fine_tuned_model_1") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/fine_tuned_model_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KalaiselvanD/fine_tuned_model_1: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/KalaiselvanD/fine_tuned_model_1/resolve/main/training_args.bin
- Command line
-
hf download hf://KalaiselvanD/fine_tuned_model_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KalaiselvanD/fine_tuned_model_1/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 255e092a1bced1ff9c2b6f4ae6977908340be19da121533d255271112a4010f1
- Size of remote file:
- 4.92 kB
- SHA256:
- 3c2b6ee0f3a3c2fc9307effe3e5a3f682267bcaf0038ced827759e06042885a4
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