Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
roberta
exbert
text-embeddings-inference
Instructions to use openai-community/roberta-base-openai-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai-community/roberta-base-openai-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="openai-community/roberta-base-openai-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("openai-community/roberta-base-openai-detector") model = AutoModelForSequenceClassification.from_pretrained("openai-community/roberta-base-openai-detector") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
#7
by raihankhan - opened
README.md
CHANGED
|
@@ -41,7 +41,7 @@ datasets:
|
|
| 41 |
|
| 42 |
#### Direct Use
|
| 43 |
|
| 44 |
-
The model is a classifier that can be used to detect text generated by GPT-2 models.
|
| 45 |
|
| 46 |
#### Downstream Use
|
| 47 |
|
|
|
|
| 41 |
|
| 42 |
#### Direct Use
|
| 43 |
|
| 44 |
+
The model is a classifier that can be used to detect text generated by GPT-2 models. However, it is strongly suggested not to use it as a ChatGPT detector for the purposes of making grave allegations of academic misconduct against undergraduates and others, as this model might it give inaccurate results in the case of ChatGPT generated input.
|
| 45 |
|
| 46 |
#### Downstream Use
|
| 47 |
|