Instructions to use Sami92/XLM-R-Large-Sensationalism-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sami92/XLM-R-Large-Sensationalism-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sami92/XLM-R-Large-Sensationalism-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sami92/XLM-R-Large-Sensationalism-Classifier") model = AutoModelForSequenceClassification.from_pretrained("Sami92/XLM-R-Large-Sensationalism-Classifier") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +0 -1
config.json
CHANGED
|
@@ -1,5 +1,4 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "/home/sami/CLAIMSPOTTING/Classification_Training/SensationalClassification/Models/xlm-finetuned/checkpoint-2118",
|
| 3 |
"architectures": [
|
| 4 |
"XLMRobertaForSequenceClassification"
|
| 5 |
],
|
|
|
|
| 1 |
{
|
|
|
|
| 2 |
"architectures": [
|
| 3 |
"XLMRobertaForSequenceClassification"
|
| 4 |
],
|