Text Classification
Transformers
Safetensors
Portuguese
distilbert
Generated from Trainer
sentiment-analysis
Instructions to use Octavio-Santana/distilbert-base-sentiment-analysis-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Octavio-Santana/distilbert-base-sentiment-analysis-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Octavio-Santana/distilbert-base-sentiment-analysis-pt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Octavio-Santana/distilbert-base-sentiment-analysis-pt") model = AutoModelForSequenceClassification.from_pretrained("Octavio-Santana/distilbert-base-sentiment-analysis-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Octavio-Santana/distilbert-base-sentiment-analysis-pt: direct link, hf CLI and curl.
- Browser
- Download file 5.14 kB
-
https://huggingface.co/Octavio-Santana/distilbert-base-sentiment-analysis-pt/resolve/main/training_args.bin
- Command line
-
hf download hf://Octavio-Santana/distilbert-base-sentiment-analysis-pt/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Octavio-Santana/distilbert-base-sentiment-analysis-pt/resolve/main/training_args.bin
5.14 kB
- Xet hash:
- 064a59362aa00e5e7ce98c640b9e1318684ab88c0473699469499030da26f96c
- Size of remote file:
- 5.14 kB
- SHA256:
- fe343d3ed880eb0030c1029c2628ba790d85022bebb892c652aac7bdbf5fbe60
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