Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 from threading import Thread
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, TextIteratorStreamer
 
-model_id = "rasyosef/gpt2-small-amharic-128-v3"
+model_id = "rasyosef/gpt2-medium-amharic-28k-512"
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id)
@@ -27,11 +27,11 @@ def generate(prompt):
       kwargs={
         "text_inputs": prompt,
         "max_new_tokens": max_new_tokens,
-        "temperature": 0.8,
+        "temperature": 0.4,
         "do_sample": True,
         "top_k": 8,
         "top_p": 0.8,
-        "repetition_penalty": 1.25,
+        "repetition_penalty": 1.4,
         "streamer": streamer
       })
     thread.start()
@@ -45,15 +45,14 @@ def generate(prompt):
 with gr.Blocks(css="#prompt_textbox textarea {color: blue}") as demo:
   gr.Markdown("""
   # GPT2 Amharic
-  This is a demo for a smaller version of OpenAI's [gpt2](https://huggingface.co/openai-community/gpt2) decoder transformer model pretrained for 1.5 days on `290 million` tokens of **Amharic** text. The context size of [gpt2-small-amharic](https://huggingface.co/rasyosef/gpt2-small-amharic-128-v3) is 128 tokens. This is a base model and hasn't undergone any supervised finetuing yet.
-
+  This is a demo for a smaller version of OpenAI's [gpt2](https://huggingface.co/openai-community/gpt2) decoder transformer model pretrained for 2 days on `290 million` tokens of **Amharic** text. The context size of [gpt2-medium-amharic](https://huggingface.co/rasyosef/gpt2-medium-amharic-28k-512) is 512 tokens. This is a base model and hasn't undergone any supervised finetuing yet.
   Please **enter a prompt** and click the **Generate** button to generate completions for the prompt.
   #### Text generation parameters:
-  - `temperature` : **0.8**
+  - `temperature` : **0.4**
   - `do_sample` : **True**
   - `top_k` : **8**
   - `top_p` : **0.8**
-  - `repetition_penalty` : **1.25**
+  - `repetition_penalty` : **1.4**
   """)
 
   prompt = gr.Textbox(label="Prompt", placeholder="Enter prompt here", lines=4, interactive=True, elem_id="prompt_textbox")