Text Classification
Transformers
ONNX
Safetensors
Transformers.js
modernbert
abacusai
toxicity
content-moderation
trust-and-safety
perspective-api
hate-speech
multi-label-classification
text-embeddings-inference
Instructions to use abacusai/Toxicity-Lens with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abacusai/Toxicity-Lens with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abacusai/Toxicity-Lens")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abacusai/Toxicity-Lens") model = AutoModelForSequenceClassification.from_pretrained("abacusai/Toxicity-Lens", device_map="auto") - Transformers.js
How to use abacusai/Toxicity-Lens with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'abacusai/Toxicity-Lens'); - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from abacusai/Toxicity-Lens: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/abacusai/Toxicity-Lens/resolve/main/tokenizer.json
- Command line
-
hf download hf://abacusai/Toxicity-Lens/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/abacusai/Toxicity-Lens/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- c93bdcedf90db5e30ccf8cefc43295c77fbf2cd123f5830478c5f550fac7e9cf
- Size of remote file:
- 34.4 MB
- SHA256:
- 0a5069feab370ece9f452dcda41c0ba2c216eebf6cb49b06893698f53cdc2b0b
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