Text Classification
Transformers
PyTorch
Italian
xlm-roberta
text classification
abusive language
hate speech
offensive language
text-embeddings-inference
Instructions to use MilaNLProc/hate-ita with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MilaNLProc/hate-ita with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MilaNLProc/hate-ita")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MilaNLProc/hate-ita") model = AutoModelForSequenceClassification.from_pretrained("MilaNLProc/hate-ita", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +4 -4
config.json
CHANGED
|
@@ -37,8 +37,8 @@
|
|
| 37 |
"non-hateful": 0,
|
| 38 |
"hateful": 1
|
| 39 |
},
|
| 40 |
-
"id2label":
|
| 41 |
-
"non-hateful",
|
| 42 |
-
"hateful"
|
| 43 |
-
|
| 44 |
}
|
|
|
|
| 37 |
"non-hateful": 0,
|
| 38 |
"hateful": 1
|
| 39 |
},
|
| 40 |
+
"id2label": {
|
| 41 |
+
0: "non-hateful",
|
| 42 |
+
1: "hateful"
|
| 43 |
+
}
|
| 44 |
}
|