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 pytorch_model.bin from gsl22/Metricas_teste2: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/gsl22/Metricas_teste2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gsl22/Metricas_teste2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gsl22/Metricas_teste2/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 0f73976c6f4d6613202c42a815657e822453960ac005e0d2164b68c760f88453
- Size of remote file:
- 268 MB
- SHA256:
- 1463fda1faf3517420ad83ef105b8c74487d6784aa5ebb6647c9e0a1f6c4389a
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