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 training_args.bin from gsl22/testando: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/gsl22/testando/resolve/main/training_args.bin
- Command line
-
hf download hf://gsl22/testando/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gsl22/testando/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- dd4db6305f156205dd17e60a21eb8a11c62960b401592be6d7f9bc38ef63d0d8
- Size of remote file:
- 3.96 kB
- SHA256:
- e8f8bf55d17bd1222fba20fd58dfb417798d7a28d6c02dadebeb63f7e143f50d
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