Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use wvangils/NL_BERT_michelin_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wvangils/NL_BERT_michelin_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wvangils/NL_BERT_michelin_finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wvangils/NL_BERT_michelin_finetuned") model = AutoModelForSequenceClassification.from_pretrained("wvangils/NL_BERT_michelin_finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files- pytorch_model.bin +1 -1
- runs/May05_13-10-01_8cd36a2f7e94/events.out.tfevents.1651756478.8cd36a2f7e94.70.0 +2 -2
- runs/May05_14-24-24_8cd36a2f7e94/1651760705.9320273/events.out.tfevents.1651760705.8cd36a2f7e94.70.3 +3 -0
- runs/May05_14-24-24_8cd36a2f7e94/events.out.tfevents.1651760705.8cd36a2f7e94.70.2 +3 -0
- training_args.bin +1 -1
pytorch_model.bin
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