Instructions to use KalaiselvanD/kala-_bert_model_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/kala-_bert_model_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/kala-_bert_model_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/kala-_bert_model_test") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/kala-_bert_model_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KalaiselvanD/kala-_bert_model_test: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/KalaiselvanD/kala-_bert_model_test/resolve/main/training_args.bin
- Command line
-
hf download hf://KalaiselvanD/kala-_bert_model_test/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KalaiselvanD/kala-_bert_model_test/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 33caeaa2e64aca1df0baea0d5718c5a5f1443ca154845172e841288559e50922
- Size of remote file:
- 4.98 kB
- SHA256:
- 9b55a8e3db5338f60330ae94b33ea59113bab196ca30cab9f3ee4127ef5b963c
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