Instructions to use Adapting/comfort_congratulations_neutral-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adapting/comfort_congratulations_neutral-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Adapting/comfort_congratulations_neutral-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Adapting/comfort_congratulations_neutral-classifier") model = AutoModelForSequenceClassification.from_pretrained("Adapting/comfort_congratulations_neutral-classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -6,5 +6,7 @@ code used to train this model: https://colab.research.google.com/drive/1BHc8UMuT
|
|
| 6 |
dataset: https://huggingface.co/datasets/Adapting/empathetic_dialogues_v2
|
| 7 |
|
| 8 |
LABEL_0: neutral
|
|
|
|
| 9 |
LABEL_1: congratulating
|
|
|
|
| 10 |
LABEL_2: comforting
|
|
|
|
| 6 |
dataset: https://huggingface.co/datasets/Adapting/empathetic_dialogues_v2
|
| 7 |
|
| 8 |
LABEL_0: neutral
|
| 9 |
+
|
| 10 |
LABEL_1: congratulating
|
| 11 |
+
|
| 12 |
LABEL_2: comforting
|