Instructions to use sgonzalezsilot/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgonzalezsilot/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgonzalezsilot/output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgonzalezsilot/output") model = AutoModelForSequenceClassification.from_pretrained("sgonzalezsilot/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sgonzalezsilot/output: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/sgonzalezsilot/output/resolve/main/training_args.bin
- Command line
-
hf download hf://sgonzalezsilot/output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sgonzalezsilot/output/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 494d44964c4d7217b5a151ffe21f3db4a6e5382e91de00c734116eafdb4d7877
- Size of remote file:
- 4.66 kB
- SHA256:
- 6de15315b953722759f5da3c5534c74e3c30299ad6cc5b88bec2a147af19af4d
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