Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use sgugger/distilbert-base-uncased-finetuned-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/distilbert-base-uncased-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgugger/distilbert-base-uncased-finetuned-cola")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgugger/distilbert-base-uncased-finetuned-cola") model = AutoModelForSequenceClassification.from_pretrained("sgugger/distilbert-base-uncased-finetuned-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sgugger/distilbert-base-uncased-finetuned-cola: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/sgugger/distilbert-base-uncased-finetuned-cola/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sgugger/distilbert-base-uncased-finetuned-cola/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sgugger/distilbert-base-uncased-finetuned-cola/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- a370c91fa52b16a025b1cc86435563ee5188a160b818bf2f43245ef1f9d2f317
- Size of remote file:
- 268 MB
- SHA256:
- aaa55597f2aaea684fdf88bd6805ff1388998cee7888da1910872786b5c25d91
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