Add model dict & set up instructions

.gitignore

@@ -1,2 +1,3 @@
 venv_sce/*
-.DS_Store
+.DS_Store
+.ipynb_checkpoints/*

README.md

@@ -12,4 +12,11 @@ pinned: false
 To link arXiv paper to this demo, reference below:
 models: https://huggingface.co/emilylearning/selection-induced-collider-bias
 
+# Setup env:
+```
+python3 -m venv venv_sce 
+source venv_sce/bin/activate 
+pip install -r requirements.txt 
+```
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

@@ -8,9 +8,21 @@ import random
 from matplotlib.ticker import MaxNLocator
 from transformers import pipeline
 
-MODEL_NAMES = ["bert-base-uncased", "roberta-base", "bert-large-uncased", "roberta-large"]
 OWN_MODEL_NAME = 'add-a-model'
 
+MODEL_NAME_DICT = {
+    "roberta-large": "RoBERTa-large",
+    "bert-large-uncased": "BERT-large",
+    "roberta-base": "RoBERTa-base",
+    "bert-base-uncased": "BERT-base",
+    "olm/olm-roberta-base-oct-2022": "OLM_RoBERTa-base",
+    OWN_MODEL_NAME: "Your model's"
+}
+MODEL_NAMES = list(MODEL_NAME_DICT.keys())
+
+# MODEL_NAMES = ["bert-base-uncased", "roberta-base", "bert-large-uncased", "roberta-large"]
+# OWN_MODEL_NAME = 'add-a-model'
+
 DECIMAL_PLACES = 1
 EPS = 1e-5  # to avoid /0 errors
 
@@ -136,10 +148,7 @@ GENDERED_LIST = [
 
 # %%
 # Fire up the models
-models = dict()
-
-for bert_like in MODEL_NAMES:
-    models[bert_like] = pipeline("fill-mask", model=bert_like)
+models = {m : pipeline("fill-mask", model=m) for m in MODEL_NAMES if m != OWN_MODEL_NAME}
 
 # %%
 
@@ -391,12 +400,11 @@ with demo:
 
 
     gr.Markdown("B) Pick a pre-loaded BERT-family model of interest on the right.")
-    gr.Markdown(f"Or C) select `{OWN_MODEL_NAME}`, then add the mame of any other Hugging Face model that supports the [fill-mask](https://huggingface.co/models?pipeline_tag=fill-mask) task on the right (note: this may take some time to load).")
+    gr.Markdown(f"Or C) select `{OWN_MODEL_NAME}`, then add the name of any other Hugging Face model that supports the [fill-mask](https://huggingface.co/models?pipeline_tag=fill-mask) task on the right (note: this may take some time to load).")
 
     with gr.Row():
         model_name = gr.Radio(
-            MODEL_NAMES + [OWN_MODEL_NAME],
-            type="value",
+            MODEL_NAMES,
             label="B) BERT-like model.",
         )
         own_model_name = gr.Textbox(
@@ -412,7 +420,6 @@ with demo:
         to_normalize = gr.Dropdown(
             ["False", "True"],
             label="D) Normalize model's predictions to only the gendered ones?",
-            type="index",
         )
         place_holder = gr.Textbox(
             label="E) Special token place-holder",
@@ -420,7 +427,6 @@ with demo:
         n_fit = gr.Dropdown(
             list(range(1, 5)),
             label="F) Degree of polynomial fit",
-            type="value",
         )
 
     gr.Markdown(
@@ -433,16 +439,15 @@ with demo:
         )
 
     gr.Markdown("## Outputs!")
-    #gr.Markdown("Scroll down and 'Hit Submit'!")
     with gr.Row():
         btn = gr.Button("Hit submit to generate predictions!")
 
     with gr.Row():
         sample_text = gr.Textbox(
-            type="auto", label="Output text: Sample of text fed to model")
+            label="Output text: Sample of text fed to model")
     with gr.Row():
-        female_fig = gr.Plot(type="auto")
-        male_fig = gr.Plot(type="auto")
+        female_fig = gr.Plot()
+        male_fig = gr.Plot()
     with gr.Row():
         df = gr.Dataframe(
             show_label=True,