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
- Xet hash:
- 06cae79ae7ea16f09c86d9041b63c772aa85408a44318c19ce0e7a2b1440ca62
- Size of remote file:
- 437 MB
- SHA256:
- 4cf373059f8e248dcc9d8878fcf4bc5cb73850cfd3b2280f66bdfb7c0dff2624
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