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
Download training_args.bin from wvangils/NL_BERT_michelin_finetuned: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/wvangils/NL_BERT_michelin_finetuned/resolve/2b77919a96a575871ccca3cc0897f0d45aa92266/training_args.bin
- Command line
-
hf download hf://wvangils/NL_BERT_michelin_finetuned@2b77919a96a575871ccca3cc0897f0d45aa92266/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/wvangils/NL_BERT_michelin_finetuned/resolve/2b77919a96a575871ccca3cc0897f0d45aa92266/training_args.bin
3.12 kB
- Xet hash:
- ee0a3a61abf3bd38ac87bb436010714475445b5a85f7780f5621249251d47873
- Size of remote file:
- 3.12 kB
- SHA256:
- 4c1d7046de31e3405889bf9aee543da24d3a55dfb44d5c88f2ef7c1b298ee8aa
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