Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use sgugger/finetuned-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/finetuned-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgugger/finetuned-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgugger/finetuned-bert") model = AutoModelForSequenceClassification.from_pretrained("sgugger/finetuned-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sgugger/finetuned-bert: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/sgugger/finetuned-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sgugger/finetuned-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sgugger/finetuned-bert/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 06a25bf0af1207a79a61b72d7d028bdf1307f943d79e73d985f4246c7aab4881
- Size of remote file:
- 433 MB
- SHA256:
- 3937f3a3cde4bca491bdb7d1415543096ac860b233a8c5465c7ce48fd952e0f8
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