Push model using huggingface_hub.

README.md

@@ -10,12 +10,11 @@ metrics:
 widget: []
 pipeline_tag: text-classification
 inference: true
-base_model: BAAI/bge-base-en-v1.5
 ---
 
-# SetFit with BAAI/bge-base-en-v1.5
+# SetFit
 
-This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
+This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
 
 The model has been trained using an efficient few-shot learning technique that involves:
 
@@ -26,10 +25,10 @@ The model has been trained using an efficient few-shot learning technique that i
 
 ### Model Description
 - **Model Type:** SetFit
-- **Sentence Transformer body:** [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)
+<!-- - **Sentence Transformer:** [Unknown](https://huggingface.co/unknown) -->
 - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
 - **Maximum Sequence Length:** 512 tokens
-<!-- - **Number of Classes:** Unknown -->
+- **Number of Classes:** 4 classes
 <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
 <!-- - **Language:** Unknown -->
 <!-- - **License:** Unknown -->

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "models/setfit_bge-base-en-v1.5/",
+  "_name_or_path": "/home/tstad/.cache/torch/sentence_transformers/tstadel_answer-classification-setfit-v2/",
   "architectures": [
     "BertModel"
   ],

config_setfit.json

@@ -1,4 +1,9 @@
 {
   "normalize_embeddings": false,
-  "labels": null
+  "labels": [
+    "needs_verification",
+    "no_answer",
+    "needs_context",
+    "noise"
+  ]
 }