Instructions to use BaoNhan/velectra-base-vifn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BaoNhan/velectra-base-vifn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BaoNhan/velectra-base-vifn")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BaoNhan/velectra-base-vifn") model = AutoModelForSequenceClassification.from_pretrained("BaoNhan/velectra-base-vifn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "status": "passed", | |
| "model_dir": "/content/drive/MyDrive/EACL_2027_ViFN_Benchmark/final_models/velectra-base-vifn", | |
| "tokenizer_class": "BertTokenizer", | |
| "model_class": "ElectraForSequenceClassification", | |
| "model_type": "electra", | |
| "probabilities": [ | |
| 0.9709103107452393, | |
| 0.029089679941534996 | |
| ], | |
| "finished_at_utc": "2026-07-18T18:08:30.486079+00:00" | |
| } |