Instructions to use VijendraUmath/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VijendraUmath/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VijendraUmath/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VijendraUmath/results") model = AutoModelForSequenceClassification.from_pretrained("VijendraUmath/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from VijendraUmath/results: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/VijendraUmath/results/resolve/main/training_args.bin
- Command line
-
hf download hf://VijendraUmath/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/VijendraUmath/results/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 172f9b93e17fd078457f6983231e7b423d1b5266b577f7a1ad8cd6c7869c499a
- Size of remote file:
- 4.86 kB
- SHA256:
- 5d55acb83f13ee482075cd8da4e1332072c3e0bc41de021d1f92da432e46d6bd
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