Instructions to use Ife/distilbert-base-uncased-finetuned-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ife/distilbert-base-uncased-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ife/distilbert-base-uncased-finetuned-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ife/distilbert-base-uncased-finetuned-cola") model = AutoModelForSequenceClassification.from_pretrained("Ife/distilbert-base-uncased-finetuned-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Ife/distilbert-base-uncased-finetuned-cola: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Ife/distilbert-base-uncased-finetuned-cola/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Ife/distilbert-base-uncased-finetuned-cola/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Ife/distilbert-base-uncased-finetuned-cola/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- d3d8be0cfeb7e55498b3b8f14a47e290f7435e93a924fdaf7dd509c0c323d600
- Size of remote file:
- 268 MB
- SHA256:
- 787127be51c65fdd52fb65e360069879adc08c1db08fd33eeefae63faa79c896
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