feat: add pytorch to deps and run pipeline directly via transformers

app.py

@@ -1,10 +1,7 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from transformers import pipeline
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient(model="pszemraj/distilgpt2-magicprompt-SD")
+pipe = pipeline("text-generation", model="pszemraj/distilgpt2-magicprompt-SD")
 
 
 def respond(
@@ -15,21 +12,14 @@ def respond(
     top_p: float,
     top_k: int
 ):
-    response = ""
-
-    for message in client.text_generation(
+    yield pipe(
         message,
         max_new_tokens=max_new_tokens,
-        stream=True,
         do_sample=True,
         temperature=temperature,
         top_p=top_p,
         top_k=top_k
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
+    )
 
 
 """

requirements.txt

@@ -1 +1,4 @@
-huggingface_hub==0.25.2
+huggingface_hub==0.25.2
+pytorch==2.7.0
+torchvision
+transformers