work on dialogue models

.gitignore

@@ -0,0 +1,2 @@
+__pycache__/*
+gradio_cached_examples/*

LICENSE.txt

@@ -1,126 +0,0 @@
-LLAMA 2 COMMUNITY LICENSE AGREEMENT	
-Llama 2 Version Release Date: July 18, 2023
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app.py

@@ -1,36 +1,24 @@
 from typing import Iterator
-
 import gradio as gr
 import torch
-
 from model import get_input_token_length, run
 
 DEFAULT_SYSTEM_PROMPT = """\
-You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe.  Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.\
+Wetin be your name ?\
 """
 MAX_MAX_NEW_TOKENS = 2048
 DEFAULT_MAX_NEW_TOKENS = 1024
 MAX_INPUT_TOKEN_LENGTH = 4000
 
 DESCRIPTION = """
-# Llama-2 13B Chat
-
-This Space demonstrates model [Llama-2-13b-chat](https://huggingface.co/meta-llama/Llama-2-13b-chat) by Meta, a Llama 2 model with 13B parameters fine-tuned for chat instructions. Feel free to play with it, or duplicate to run generations without a queue! If you want to run your own service, you can also [deploy the model on Inference Endpoints](https://huggingface.co/inference-endpoints).
-
-🔎 For more details about the Llama 2 family of models and how to use them with `transformers`, take a look [at our blog post](https://huggingface.co/blog/llama2).
-
-🔨 Looking for an even more powerful model? Check out the large [**70B** model demo](https://huggingface.co/spaces/ysharma/Explore_llamav2_with_TGI).
-🐇 For a smaller model that you can run on many GPUs, check our [7B model demo](https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat).
+# Masakhane Dialogue Models
+This Space demonstrates the dialogue models for Nigerian Pidgin, an African langage.\
+🔎 For more about visit [our homepage](https://www.masakhane.io/).
 
 """
+#🔨 Looking for an even more powerful model? Check out the large [**70B** model demo](https://huggingface.co/spaces/ysharma/Explore_llamav2_with_TGI).
+#🐇 For a smaller model that you can run on many GPUs, check our [7B model demo](https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat).
 
-LICENSE = """
-<p/>
-
----
-As a derivate work of [Llama-2-13b-chat](https://huggingface.co/meta-llama/Llama-2-13b-chat) by Meta,
-this demo is governed by the original [license](https://huggingface.co/spaces/huggingface-projects/llama-2-13b-chat/blob/main/LICENSE.txt) and [acceptable use policy](https://huggingface.co/spaces/huggingface-projects/llama-2-13b-chat/blob/main/USE_POLICY.md).
-"""
 
 if not torch.cuda.is_available():
     DESCRIPTION += '\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>'
@@ -93,8 +81,8 @@ def check_input_token_length(message: str, chat_history: list[tuple[str, str]],
 
 with gr.Blocks(css='style.css') as demo:
     gr.Markdown(DESCRIPTION)
-    gr.DuplicateButton(value='Duplicate Space for private use',
-                       elem_id='duplicate-button')
+    #gr.DuplicateButton(value='Duplicate Space for private use',
+    #                   elem_id='duplicate-button')
 
     with gr.Group():
         chatbot = gr.Chatbot(label='Chatbot')
@@ -110,9 +98,9 @@ with gr.Blocks(css='style.css') as demo:
                                       scale=1,
                                       min_width=0)
     with gr.Row():
-        retry_button = gr.Button('🔄  Retry', variant='secondary')
+        retry_button = gr.Button('🔄 Retry', variant='secondary')
         undo_button = gr.Button('↩️ Undo', variant='secondary')
-        clear_button = gr.Button('🗑️  Clear', variant='secondary')
+        clear_button = gr.Button('🗑️ Clear', variant='secondary')
 
     saved_input = gr.State()
 
@@ -151,11 +139,10 @@ with gr.Blocks(css='style.css') as demo:
 
     gr.Examples(
         examples=[
-            'Hello there! How are you doing?',
-            'Can you explain briefly to me what is the Python programming language?',
-            'Explain the plot of Cinderella in a sentence.',
-            'How many hours does it take a man to eat a Helicopter?',
-            "Write a 100-word article on 'Benefits of Open-Source in AI research'",
+            'How I fit chop for here?',
+            'I hear say restaurant dey here.',
+            'Abeg you fit tell me which kind chop dey?',
+            'I dey find restauarant.',
         ],
         inputs=textbox,
         outputs=[textbox, chatbot],
@@ -163,7 +150,7 @@ with gr.Blocks(css='style.css') as demo:
         cache_examples=True,
     )
 
-    gr.Markdown(LICENSE)
+    #gr.Markdown(LICENSE)
 
     textbox.submit(
         fn=clear_and_save_textbox,

model.py

@@ -1,10 +1,9 @@
 from threading import Thread
 from typing import Iterator
-
 import torch
 from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
 
-model_id = 'meta-llama/Llama-2-13b-chat-hf'
+model_id = 'tosin/dialogpt_afriwoz_pidgin'
 
 if torch.cuda.is_available():
     config = AutoConfig.from_pretrained(model_id)
@@ -23,15 +22,18 @@ tokenizer = AutoTokenizer.from_pretrained(model_id)
 
 def get_prompt(message: str, chat_history: list[tuple[str, str]],
                system_prompt: str) -> str:
-    texts = [f'<s>[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n']
+    #texts = [f'<s>[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n']
+    texts = [system_prompt]
     # The first user input is _not_ stripped
     do_strip = False
     for user_input, response in chat_history:
         user_input = user_input.strip() if do_strip else user_input
         do_strip = True
-        texts.append(f'{user_input} [/INST] {response.strip()} </s><s>[INST] ')
+        #texts.append(f'{user_input} [/INST] {response.strip()} </s><s>[INST] ')
+        texts.append(user_input)
+        texts.append(response.strip())
     message = message.strip() if do_strip else message
-    texts.append(f'{message} [/INST]')
+    texts.append(message)
     return ''.join(texts)