feat: add scademy models

.gitignore

@@ -1,2 +1,3 @@
 venv
 flagged
+.env

app.py

@@ -1,15 +1,34 @@
 import gradio as gr
 from transformers import pipeline
+import os
+from dotenv import load_dotenv
 
-raw_model_name = 'distilbert-base-uncased'
-raw_model = pipeline('sentiment-analysis', model=raw_model_name)
-fine_tuned_model_name = 'distilbert-base-uncased-finetuned-sst-2-english'
-fine_tuned_model = pipeline('sentiment-analysis', model=fine_tuned_model_name)
+load_dotenv()
+token = os.environ.get("HF_TOKEN")
+
+raw_model_name = "distilbert-base-uncased"
+raw_model = pipeline("sentiment-analysis", model=raw_model_name)
+
+scademy_500_500_model_name = "scademy/bert-finetuned-500-500-0"
+scademy_500_500_model = pipeline("sentiment-analysis", model=scademy_500_500_model_name, token=token)
+
+scademy_2500_2500_model_name = "scademy/bert-finetuned-2500-2500-0"
+scademy_2500_2500_model = pipeline("sentiment-analysis", model=scademy_2500_2500_model_name, token=token)
+
+fine_tuned_model_name = "distilbert-base-uncased-finetuned-sst-2-english"
+fine_tuned_model = pipeline("sentiment-analysis", model=fine_tuned_model_name)
 
 def get_model_output(input_text, model_choice):
     raw_result = raw_model(input_text)
+    scademy_500_500_result = scademy_500_500_model(input_text)
+    scademy_2500_2500_result = scademy_2500_2500_model(input_text)
     fine_tuned_result = fine_tuned_model(input_text)
-    return format_model_output(raw_result[0]), format_model_output(fine_tuned_result[0])
+    return (
+        format_model_output(raw_result[0]),
+        format_model_output(scademy_500_500_result[0]),
+        format_model_output(scademy_2500_2500_result[0]),
+        format_model_output(fine_tuned_result[0])
+    )
 
 def format_model_output(output):
     return f"I am {output['score']*100:.2f}% sure that the sentiment is {output['label']}"
@@ -22,7 +41,9 @@ iface = gr.Interface(
     ],
     outputs=[
         gr.Textbox(label="Base DistilBERT output (distilbert-base-uncased)"),
-        gr.Textbox(label="Fine-tuned DistilBERT output")
+        gr.Textbox(label="Scademy DistilBERT 500-500 output"),
+        gr.Textbox(label="Scademy DistilBERT 2500-2500 output"),
+        gr.Textbox(label="Fine-tuned DistilBERT output"),
     ],
 )
 

requirements.txt

@@ -1,7 +1,10 @@
 aiofiles==23.2.1
+aiohttp==3.9.0
+aiosignal==1.3.1
 altair==5.1.2
 annotated-types==0.6.0
 anyio==3.7.1
+async-timeout==4.0.3
 attrs==23.1.0
 certifi==2023.11.17
 charset-normalizer==3.3.2
@@ -9,11 +12,14 @@ click==8.1.3
 colorama==0.4.6
 contourpy==1.2.0
 cycler==0.12.1
+datasets==2.15.0
+dill==0.3.7
 exceptiongroup==1.2.0
 fastapi==0.104.1
 ffmpy==0.3.1
 filelock==3.13.1
 fonttools==4.45.0
+frozenlist==1.4.0
 fsspec==2023.10.0
 gradio==4.5.0
 gradio_client==0.7.0
@@ -32,12 +38,16 @@ MarkupSafe==2.1.3
 matplotlib==3.8.2
 mdurl==0.1.2
 mpmath==1.3.0
+multidict==6.0.4
+multiprocess==0.70.15
 networkx==3.2.1
 numpy==1.26.2
 orjson==3.9.10
 packaging==23.2
 pandas==2.1.3
 Pillow==10.1.0
+pyarrow==14.0.1
+pyarrow-hotfix==0.5
 pydantic==2.5.1
 pydantic_core==2.14.3
 pydub==0.25.1
@@ -45,6 +55,7 @@ Pygments==2.17.1
 pyparsing==3.1.1
 pystache==0.6.0
 python-dateutil==2.8.2
+python-dotenv==1.0.0
 python-multipart==0.0.6
 pytz==2023.3.post1
 PyYAML==6.0.1
@@ -72,3 +83,5 @@ tzdata==2023.3
 urllib3==2.1.0
 uvicorn==0.24.0.post1
 websockets==11.0.3
+xxhash==3.4.1
+yarl==1.9.3