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/llama-3.2-amharic-28k-512"
+model_id = "rasyosef/llama-3.2-amharic-64k-1024"
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id)
@@ -24,11 +24,11 @@ def generate(prompt):
         "inputs": inputs["input_ids"],
         "attention_mask": inputs["attention_mask"],
         "max_new_tokens": max_new_tokens,
-        "temperature": 0.4,
+        "temperature": 0.3,
         "do_sample": True,
         "top_k": 8,
         "top_p": 0.8,
-        "repetition_penalty": 1.4,
+        "repetition_penalty": 1.25,
         "streamer": streamer,
         "pad_token_id": tokenizer.pad_token_id,
         "eos_token_id": tokenizer.eos_token_id
@@ -44,15 +44,15 @@ def generate(prompt):
 with gr.Blocks(css="#prompt_textbox textarea {color: blue}") as demo:
   gr.Markdown("""
   # Llama 3.2 Amharic
-  This is a demo for [llama-3.2-amharic](https://huggingface.co/rasyosef/llama-3.2-amharic-28k-512), a smaller version of Meta's [Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) decoder transformer model pretrained for 1.5 days on `276 million` tokens of **Amharic** text. This model has `155 million` parameters and a context size of `512` tokens. This is a base model and hasn't undergone any supervised finetuing yet.
+  This is a demo for [llama-3.2-amharic](https://huggingface.co/rasyosef/llama-3.2-amharic-64k-1024), a smaller version of Meta's [Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) decoder transformer model pretrained for 3 days on `210 million` tokens of **Amharic** text. This model has `179 million` parameters and a context size of `1024` 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` : **0.4**
+  - `temperature` : **0.3**
   - `do_sample` : **True**
   - `top_k` : **8**
   - `top_p` : **0.8**
-  - `repetition_penalty` : **1.4**
+  - `repetition_penalty` : **1.25**
   """)
 
   prompt = gr.Textbox(label="Prompt", placeholder="Enter prompt here", lines=4, interactive=True, elem_id="prompt_textbox")