Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use gsl22/Metricas_teste with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsl22/Metricas_teste with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gsl22/Metricas_teste")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gsl22/Metricas_teste") model = AutoModelForSequenceClassification.from_pretrained("gsl22/Metricas_teste", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gsl22/Metricas_teste: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/gsl22/Metricas_teste/resolve/main/training_args.bin
- Command line
-
hf download hf://gsl22/Metricas_teste/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gsl22/Metricas_teste/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- d6675ee408f5985125c571f0cc79473364509da996d3ca1b5e89646f9c6c030d
- Size of remote file:
- 3.96 kB
- SHA256:
- 974f28d77db34e6cbc3b746e3aff7a319a64fc90579d5aff3d345608ad9ad430
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