Instructions to use tanganke/gpt2_rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanganke/gpt2_rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tanganke/gpt2_rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tanganke/gpt2_rte") model = AutoModelForSequenceClassification.from_pretrained("tanganke/gpt2_rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download results.csv from tanganke/gpt2_rte: direct link, hf CLI and curl.
- Browser
- Download file 155 Bytes
-
https://huggingface.co/tanganke/gpt2_rte/resolve/dcd99d391850e5581b458620ce8a9c4e02ff6fec/results.csv
- Command line
-
hf download hf://tanganke/gpt2_rte@dcd99d391850e5581b458620ce8a9c4e02ff6fec/results.csv
-
curl -L -o results.csv https://huggingface.co/tanganke/gpt2_rte/resolve/dcd99d391850e5581b458620ce8a9c4e02ff6fec/results.csv
155 Bytes
| mrpc,mnli,cola,sst2,qnli,qqp,rte | |
| 0.375,0.47692307692307695,0.5282837967401726,0.5493119266055045,0.5352370492403441,0.33670541676972543,0.6534296028880866 | |