Text Classification
Transformers
Safetensors
English
modernbert
wikipedia
enwiki
text-embeddings-inference
Instructions to use derenrich/wiki-kid-friendly-classification-pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use derenrich/wiki-kid-friendly-classification-pipeline with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="derenrich/wiki-kid-friendly-classification-pipeline")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("derenrich/wiki-kid-friendly-classification-pipeline") model = AutoModelForSequenceClassification.from_pretrained("derenrich/wiki-kid-friendly-classification-pipeline") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,8 +1,13 @@
|
|
| 1 |
---
|
| 2 |
library_name: transformers
|
| 3 |
-
tags:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4 |
---
|
| 5 |
-
|
| 6 |
This model takes an English Wikipedia article and tries to decide if the topic is kid-friendly. If it is not it assigns to one of the categories: crime, terrorism, political, mental health, controvserial, disaster, sex, drugs
|
| 7 |
|
| 8 |
The model is not vetted for accuracy or bias. Anecdotally it seems to perform well though it may be overly sensistive and it is likely biased. Mainly meant for prototypes where you don't yet know how you need to be filtering before making a more complete model.
|
|
|
|
| 1 |
---
|
| 2 |
library_name: transformers
|
| 3 |
+
tags:
|
| 4 |
+
- wikipedia
|
| 5 |
+
- enwiki
|
| 6 |
+
language:
|
| 7 |
+
- en
|
| 8 |
+
base_model:
|
| 9 |
+
- answerdotai/ModernBERT-base
|
| 10 |
---
|
|
|
|
| 11 |
This model takes an English Wikipedia article and tries to decide if the topic is kid-friendly. If it is not it assigns to one of the categories: crime, terrorism, political, mental health, controvserial, disaster, sex, drugs
|
| 12 |
|
| 13 |
The model is not vetted for accuracy or bias. Anecdotally it seems to perform well though it may be overly sensistive and it is likely biased. Mainly meant for prototypes where you don't yet know how you need to be filtering before making a more complete model.
|