all models

app.py

@@ -1,8 +1,11 @@
 import gradio as gr
-from transformers import AutoModelForCausalLM, pipeline
+from transformers import pipeline
+from huggingface_hub import HfApi, ModelFilter
 
-# Define the list of model names
-models = ["gia-project/gia2-small-untrained", "gpt2"]  # Add more model names as needed
+# Get the list of models from the Hugging Face Hub
+api = HfApi()
+models = api.list_models(author="gia-project", filter=ModelFilter(tags="text-generation"))
+models_names = [model.modelId for model in models]
 
 # Dictionary to store loaded models and their pipelines
 model_pipelines = {}
@@ -28,7 +31,7 @@ def generate_text(model_name, input_text):
 iface = gr.Interface(
     fn=generate_text,  # Function to be called on user input
     inputs=[
-        gr.inputs.Dropdown(choices=models, label="Select Model", default=default_model_name),  # Dropdown to select model
+        gr.inputs.Dropdown(choices=models_names, label="Select Model", default=default_model_name),  # Dropdown to select model
         gr.inputs.Textbox(lines=5, label="Input Text")  # Textbox for entering text
     ],
     outputs=gr.outputs.Textbox(label="Generated Text"),  # Textbox to display the generated text

requirements.txt

@@ -1,2 +1,3 @@
 transformers
-torch
+torch
+huggingface_hub