
`bert-base-uncased`, fine tuned on the debiased NLI dataset from "Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets", Wu et al., 2022.

Tuned using the code at https://github.com/jimmycode/gen-debiased-nli

{"license": "apache-2.0", "widget": [{"text": "[CLS] Rover is a dog. [SEP] Rover is a cat. [SEP]"}]}
transformers pytorch safetensors bert text-classification license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #bert #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


'bert-base-uncased', fine tuned on the debiased NLI dataset from "Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets", Wu et al., 2022.

Tuned using the code at URL

TAGS
#transformers #pytorch #safetensors #bert #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #safetensors #bert #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
