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 pytorch_model.bin from gsl22/Metricas_teste: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/gsl22/Metricas_teste/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gsl22/Metricas_teste/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gsl22/Metricas_teste/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 108e55474b95fe8bfe079b4160e00dd7e08fc2136a12db55ae78341323a01a4d
- Size of remote file:
- 268 MB
- SHA256:
- 285bf685744362a08152a3780a5366d0fb069c3a0aeb0f01e431bff752a27237
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