Instructions to use santoshvutukuri/test_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use santoshvutukuri/test_train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="santoshvutukuri/test_train")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("santoshvutukuri/test_train") model = AutoModelForSequenceClassification.from_pretrained("santoshvutukuri/test_train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from santoshvutukuri/test_train: direct link, hf CLI and curl.
- Browser
- Download file 4.34 kB
-
https://huggingface.co/santoshvutukuri/test_train/resolve/main/training_args.bin
- Command line
-
hf download hf://santoshvutukuri/test_train/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/santoshvutukuri/test_train/resolve/main/training_args.bin
4.34 kB
- Xet hash:
- 7755aa2b73a98381eceb2f26d3e59ba62ff16a1019a6f2f3369f82719ef619ec
- Size of remote file:
- 4.34 kB
- SHA256:
- 6737272a684ba6f1e7e745b9ba4a9c074eca6cab9f072847ab2b479c3f677b54
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