Instructions to use gsl22/Metricas_teste2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsl22/Metricas_teste2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gsl22/Metricas_teste2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gsl22/Metricas_teste2") model = AutoModelForSequenceClassification.from_pretrained("gsl22/Metricas_teste2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gsl22/Metricas_teste2: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/gsl22/Metricas_teste2/resolve/main/training_args.bin
- Command line
-
hf download hf://gsl22/Metricas_teste2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gsl22/Metricas_teste2/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- f97c8520d2074d631d41b58de51c5c9f30a4877d20c05f800c02b7f3af53f060
- Size of remote file:
- 3.9 kB
- SHA256:
- 4b30db5a043824ee7979cde68780f872edfdddcf202afe2d9c91a83ecd0e8486
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