Text Classification
Transformers
TensorBoard
Safetensors
Portuguese
English
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use Adilmar/caramelo-smile with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adilmar/caramelo-smile with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Adilmar/caramelo-smile")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Adilmar/caramelo-smile") model = AutoModelForSequenceClassification.from_pretrained("Adilmar/caramelo-smile", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Adilmar/caramelo-smile: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/Adilmar/caramelo-smile/resolve/main/training_args.bin
- Command line
-
hf download hf://Adilmar/caramelo-smile/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Adilmar/caramelo-smile/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 6d317025749d0093abe899710354eb4e0559488b80278c67479b1db7d46c7d3f
- Size of remote file:
- 4.98 kB
- SHA256:
- 88bdd93e253f8b69a25f8d7e0189d9c0aa3b2a09a7a7ec45508840ce4a8a350b
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