no idea what i'm doing, but doing it!

app.py

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+import torch
+import gradio as gr
+import requests
+import os 
+import transformers
+from transformers import AutoModelWithLMHead, AutoTokenizer, AutoModelForCausalLM, pipeline
+from transformers import GPT2Tokenizer, GPT2Model
+
+tokenizer = AutoTokenizer.from_pretrained("href/gpt2-schiappa")
+
+model = AutoModelForCausalLM.from_pretrained("href/gpt2-schiappa")
+pipe = pipeline('text-generation', model="href/gpt2-schiappa", tokenizer=tokenizer)
+
+def text_generation(input_text, seed, min_length, max_length, temperature, top_k, top_p, repetition_penalty):
+  input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+  torch.manual_seed(seed) # Max value: 18446744073709551615
+  outputs = model.generate(input_ids, do_sample=True, max_length=max_length, min_length=min_length, temperature=temperature, top_k=top_k, top_p=top_p, repetition_penalty=repetition_penalty)
+  generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+  return generated_text
+
+title = "Minelli"
+description = "Écrit comme Marie Minelli"
+
+gr.Interface(
+    text_generation,
+    [
+      gr.inputs.Textbox(lines=2, label="Prompt"),
+      gr.inputs.Number(default=10, label="Enter seed number"),
+      gr.inputs.Slider(default=0, label="Minimum Length", minimum=0),
+      gr.inputs.Slider(default=100, label="Maximum Length", minimum=0),
+      gr.inputs.Slider(default=1.0, label="Temperature", minimum=0.1),
+      gr.inputs.Slider(default=40, label="topK", minimum=1),
+      gr.inputs.Slider(default=0.9, label="topP", minimum=0.0, maximum=1.0),
+      gr.inputs.Slider(default=1.0, label="Repetition penalty", minimum=1.0)
+    ],
+    [gr.outputs.Textbox(type="auto", label="Generated")],
+    title=title,
+    description=description,
+    theme="huggingface"
+).launch()
+

requirements.txt

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+torch
+transformers
+gradio