Update README.md

README.md

@@ -11,7 +11,7 @@ datasets:
 
 # 😵‍💫🦙 Alpaca HalluciHunter
 
-This is a cross-lingual SetFit model to **detect bad instructions from Alpaca Datasets** and potentially other instruction-following datasets. This model can greatly speed up the validation of Alpaca Datasets, flagging examples that need to be fixed or simply discarded.
+This is a cross-lingual SetFit model to **detect bad instructions from Alpaca Datasets** and potentially other instruction-following datasets. This model can greatly speed up the validation of Alpaca Datasets across many languages, flagging examples that need to be fixed or simply discarded.
 
 
 <div style="text-align:center">
@@ -25,6 +25,26 @@ It's a binary classifier with two labels:
 - `ALL GOOD`, a given instruction, input, and output are correct,
 - `BAD INSTRUCTION`, there's an issue with the instruction, and/or input and output.
 
+This model can be used as follows (see full usage instructions below):
+
+```python
+from setfit import SetFitModel
+
+# Download from Hub
+model = SetFitModel.from_pretrained("argilla/alpaca-hallucihunter-multilingual")
+
+text = """
+INSTRUCTION: 
+Gebt mir drei Adjektive, um dieses Foto zu beschreiben.
+INPUT: 
+[photo]
+OUTPUT: 
+Auffällig, lebhaft, ruhig.
+"""
+model.predict([text])
+```
+Output: `BAD INSTRUCTION`
+
 
 ## Usage
 
@@ -65,7 +85,7 @@ Load the model:
 from setfit import SetFitModel
 
 # Download from Hub
-model = SetFitModel.from_pretrained("argilla/alpaca-hallucihunter-multilingual ")
+model = SetFitModel.from_pretrained("argilla/alpaca-hallucihunter-multilingual")
 ```
 
 Perform inference and prediction col to your dataset:
@@ -124,7 +144,6 @@ Here are some examples of highest scored examples of `BAD INSTRUCTION`.
 
 
 
-
 ## BibTeX entry and citation info
 
 ```bibtex