Instructions to use amrtweg/Actora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amrtweg/Actora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amrtweg/Actora")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("amrtweg/Actora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -23,6 +23,9 @@ license: mit
|
|
| 23 |
- **Marketing Campaign Analysis**: Evaluate campaign effectiveness via predicted engagement.
|
| 24 |
- **Content Classification**: Classify content by engagement probability.
|
| 25 |
|
|
|
|
|
|
|
|
|
|
| 26 |
## Installation
|
| 27 |
|
| 28 |
```bash
|
|
|
|
| 23 |
- **Marketing Campaign Analysis**: Evaluate campaign effectiveness via predicted engagement.
|
| 24 |
- **Content Classification**: Classify content by engagement probability.
|
| 25 |
|
| 26 |
+
## Note
|
| 27 |
+
Our model delivers accuracy ranging from high to reasonable, and hallucinations may occur, which is normal in early versions of models of this type and will be continuously improved in future releases.
|
| 28 |
+
|
| 29 |
## Installation
|
| 30 |
|
| 31 |
```bash
|