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:
- f136fbd4ea9c989dbc503f1f04a626b735a46b8f08789d1b2f35641494b237ac
- Size of remote file:
- 3.12 kB
- SHA256:
- c1e83207e7d9f6f7f6c7eb568821095f4742ccd3f30b6d0d13c2771c154b225d
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