Text Classification
Transformers
PyTorch
Safetensors
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Jorgeutd/bert-base-uncased-finetuned-surveyclassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jorgeutd/bert-base-uncased-finetuned-surveyclassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jorgeutd/bert-base-uncased-finetuned-surveyclassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jorgeutd/bert-base-uncased-finetuned-surveyclassification") model = AutoModelForSequenceClassification.from_pretrained("Jorgeutd/bert-base-uncased-finetuned-surveyclassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f16b26396daec3e468a4ed1d12804fa20faaeeee2096676e5f0ec7a1cc3ae6a
- Size of remote file:
- 438 MB
- SHA256:
- ec7f6d8b9c4903576327d5c541d45efa9edd36f928342440c5e1078f02c27e50
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