Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use nickprock/distilbert-base-uncased-banking77-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickprock/distilbert-base-uncased-banking77-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nickprock/distilbert-base-uncased-banking77-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nickprock/distilbert-base-uncased-banking77-classification") model = AutoModelForSequenceClassification.from_pretrained("nickprock/distilbert-base-uncased-banking77-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nickprock/distilbert-base-uncased-banking77-classification: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/nickprock/distilbert-base-uncased-banking77-classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nickprock/distilbert-base-uncased-banking77-classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nickprock/distilbert-base-uncased-banking77-classification/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- c712fb1a54264f3a3e555ec8bbc13fd101103ca72fa432132818bf915d1d956b
- Size of remote file:
- 268 MB
- SHA256:
- d509855a3cffd0dd0059b6b20c4e5273851e3ed5554d0790b4fbf156fa45d32a
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