Instructions to use gsl22/Metricas_teste8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsl22/Metricas_teste8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gsl22/Metricas_teste8")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gsl22/Metricas_teste8") model = AutoModelForSequenceClassification.from_pretrained("gsl22/Metricas_teste8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gsl22/Metricas_teste8: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/gsl22/Metricas_teste8/resolve/main/training_args.bin
- Command line
-
hf download hf://gsl22/Metricas_teste8/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gsl22/Metricas_teste8/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 06e432151c54c55f926b43dabd10210b9e0aa86972bdd603d6b82e45f92a7ccb
- Size of remote file:
- 3.96 kB
- SHA256:
- 6963719074ad6b9f565fd1de99d37f305031ba8fd30739fd8e71e018706730c1
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