Text Classification
Transformers
PyTorch
Tagalog
English
roberta
Generated from Trainer
tagalog
filipino
twitter
text-embeddings-inference
Instructions to use mapsoriano/roberta-tagalog-base-philippine-elections-2016-2022-hate-speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mapsoriano/roberta-tagalog-base-philippine-elections-2016-2022-hate-speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mapsoriano/roberta-tagalog-base-philippine-elections-2016-2022-hate-speech")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mapsoriano/roberta-tagalog-base-philippine-elections-2016-2022-hate-speech") model = AutoModelForSequenceClassification.from_pretrained("mapsoriano/roberta-tagalog-base-philippine-elections-2016-2022-hate-speech") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c9ebd98f90b0bdf73b979b73b9b85e6247221873408d1b246221803b7dcaf45
- Size of remote file:
- 4.09 kB
- SHA256:
- b6456cf37668f95dfe674108574ea132318ea5013c18fee99ea1416a4a7d09ce
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