Instructions to use Osiris/neutral_non_neutral_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Osiris/neutral_non_neutral_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Osiris/neutral_non_neutral_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Osiris/neutral_non_neutral_classifier") model = AutoModelForSequenceClassification.from_pretrained("Osiris/neutral_non_neutral_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -7,4 +7,5 @@ LABEL_0: Neutral (have no emotion)
|
|
| 7 |
```python
|
| 8 |
>>> from transformers import pipeline
|
| 9 |
>>> nnc = pipeline('sentiment-analysis', model='distilbert-base-uncased')
|
| 10 |
-
>>> nnc("Hello, I'm a good model.")
|
|
|
|
|
|
| 7 |
```python
|
| 8 |
>>> from transformers import pipeline
|
| 9 |
>>> nnc = pipeline('sentiment-analysis', model='distilbert-base-uncased')
|
| 10 |
+
>>> nnc("Hello, I'm a good model.")
|
| 11 |
+
```
|