Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use gsl22/testando with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsl22/testando with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gsl22/testando")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gsl22/testando") model = AutoModelForSequenceClassification.from_pretrained("gsl22/testando", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gsl22/testando: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/gsl22/testando/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gsl22/testando/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gsl22/testando/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 3407a08ebc2f65d2f87b39de39bebb67daa8ed1c11b27e34a7de3ab24d41d25e
- Size of remote file:
- 268 MB
- SHA256:
- aca678c0fb3daf0e2dbf1cc12de13fab7380c449fd98c681e89f4958c342ae65
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