Instructions to use ggpt1006/tl-hate-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ggpt1006/tl-hate-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ggpt1006/tl-hate-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ggpt1006/tl-hate-bert") model = AutoModelForSequenceClassification.from_pretrained("ggpt1006/tl-hate-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
language:
- tl
metrics:
- accuracy
pipeline_tag: text-classification
library_name: transformers
datasets:
- mapsoriano/2016_2022_hate_speech_filipino
- mginoben/tagalog-profanity-dataset
- syke9p3/multilabel-tagalog-hate-speech
Model Card
- Task: Text Classification
- Use Case: Hate Speech Detection
language: "tl"
tags:
- "text-classification"
- "hate-speech"
- "nlp"
license: ""
model-index:
- name: "default"
task: "text-classification"