Update README.md

README.md

@@ -1,49 +1,27 @@
----
-license: apache-2.0
-tags:
-- setfit
-- sentence-transformers
-- text-classification
-pipeline_tag: text-classification
----
-
 # johnpaulbin/toxic-MiniLM-L6-H384-uncased
+Test if a sentence is toxic. Only works for english sentences.
 
-This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
-
-1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
-2. Training a classification head with features from the fine-tuned Sentence Transformer.
 
 ## Usage
 
-To use this model for inference, first install the SetFit library:
-
-```bash
-python -m pip install setfit
-```
+Basic classification. Labels: [NOT TOXIC, TOXIC]
 
-You can then run inference as follows:
+Install setfit
+`!pip install setfit`
 
 ```python
 from setfit import SetFitModel
 
-# Download from Hub and run inference
-model = SetFitModel.from_pretrained("johnpaulbin/toxic-MiniLM-L6-H384-uncased")
-# Run inference
-preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])
-```
+model = SetFitModel.from_pretrained("johnpaulbin/beanbox-toxic")
+
+inpt = "" #@param {type:"string"}
+
+out = model.predict_proba([inpt])
+
+if out[0][0] > out[0][1]:
+    print("Not toxic")
+else:
+    print("Toxic!")
 
-## BibTeX entry and citation info
-
-```bibtex
-@article{https://doi.org/10.48550/arxiv.2209.11055,
-doi = {10.48550/ARXIV.2209.11055},
-url = {https://arxiv.org/abs/2209.11055},
-author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
-keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
-title = {Efficient Few-Shot Learning Without Prompts},
-publisher = {arXiv},
-year = {2022},
-copyright = {Creative Commons Attribution 4.0 International}
-}
+print(f"NOT TOXIC: {out[0][0]}\nTOXIC: {out[0][1]}")
 ```