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 pytorch_model.bin from gsl22/Metricas_teste8: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/gsl22/Metricas_teste8/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gsl22/Metricas_teste8/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gsl22/Metricas_teste8/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 745fa9eb6db8f4c2918de31c1a4baad263e7374ced99c88a541c6b070b2d12a8
- Size of remote file:
- 268 MB
- SHA256:
- f23f3f5d65a49824383ee3c0c59a27a372fa6fcca34c69356733874ffb9e38ca
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