Push model using huggingface_hub. (#2)

- Push model using huggingface_hub. (58861a5d5cc7bc4cad1eba2c8f30685be48a94ab)

README.md

@@ -7,7 +7,7 @@ tags:
 pipeline_tag: text-classification
 ---
 
-# /var/folders/mt/147vhq713f1_gmbpccrp4hc00000gn/T/tmpccgvzrwb/ishan/initial-model
+# /var/folders/mt/147vhq713f1_gmbpccrp4hc00000gn/T/tmp3usg6cbk/ishan/initial-model
 
 This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
 
@@ -28,7 +28,7 @@ You can then run inference as follows:
 from setfit import SetFitModel
 
 # Download from Hub and run inference
-model = SetFitModel.from_pretrained("/var/folders/mt/147vhq713f1_gmbpccrp4hc00000gn/T/tmpccgvzrwb/ishan/initial-model")
+model = SetFitModel.from_pretrained("/var/folders/mt/147vhq713f1_gmbpccrp4hc00000gn/T/tmp3usg6cbk/ishan/initial-model")
 # Run inference
 preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])
 ```

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "/Users/ishan/Documents/models/ANSWER_QUESTION_REPEAT/",
+  "_name_or_path": "/Users/ishan/Documents/models/ANSWER_QUESTION_REPEAT/model/",
   "architectures": [
     "MPNetModel"
   ],

model_head.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9ae60bf042b1467f9acba399905c0b0499d156260661fa4838663bf5acb82ac8
+oid sha256:cbb90cb7b21e073403c44811793d88d1d791b9d3b09cf539133622b02d6856df
 size 19311

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e3cb16339b6e6ba41a97d54a9a9c62fbf2b6818b2c096a546d38f35a16322b9f
+oid sha256:8a4935f5284b18c44b64b0ac4e6ffa333d32d117117d54db04ae7e442ef37883
 size 438013677