Modifify eng/gl interface

README.md

@@ -10,4 +10,4 @@ pinned: false
 license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -3,45 +3,35 @@ import gradio as gr
 from gradio.components import Slider
 import torch
 from transformers import pipeline
-import pandas as pd
 
 # Model, information and examples ----------------------------------------------
 MODEL_NAMES = ["FLOR-1.3B-GL","Cerebras-1.3B-GL"]
-markdown_description_en = """
-# Galician LLMs
-
-
-This space contains the Galician language models developed by [Proxecto Nós](https://nos.gal/en/proxecto-nos).
-
-
-💐 **[FLOR-1.3B-GL](https://huggingface.co/proxectonos/FLOR-1.3B-GL)** is a 1.3B parameters model which is a Continual pretraining from [FLOR-1.3B](https://huggingface.co/projecte-aina/FLOR-1.3B), which is based in [Bloom 1.7B](https://huggingface.co/bigscience/bloom-1b7).
-
-👀 **Learn more about FLOR-1.3B-GL:** [HF official model card](https://huggingface.co/proxectonos/FLOR-1.3B-GL).
-
-
-🧠 **[Cerebras-1.3B-GL](https://huggingface.co/proxectonos/Cerebras-1.3B-GL)** is a 1.3B parameters model based in [Cerebras-GPT 1.3B](https://huggingface.co/cerebras/Cerebras-GPT-1.3B).
-
-👀 **Learn more about Cerebras-1.3B-GL:** [HF official model card](https://huggingface.co/proxectonos/Cerebras-1.3B-GL)
-"""
-
-markdown_description_gl = """
-# LLMs de galego
+markdown_description = """
+# LLMs de galego / Galician LLMs
 
 
 Este espazo contén diferentes Grandes Modelos da Linguaxe feitos para o galego desenvolvidos polo [Proxecto Nós](https://nos.gal/en/proxecto-nos).
 
+*This space contains the Galician language models developed by [Proxecto Nós](https://nos.gal/en/proxecto-nos).*
 
 💐 **[FLOR-1.3B-GL](https://huggingface.co/proxectonos/FLOR-1.3B-GL)** é un modelo de parámetros 1.3B que é un preadestramento continuo de [FLOR-1.3B]( https://huggingface.co/projecte-aina/FLOR-1.3B), baseado a súa vez en [Bloom 1.7B](https://huggingface.co/bigscience/bloom-1b7).
 
+*💐 **[FLOR-1.3B-GL](https://huggingface.co/proxectonos/FLOR-1.3B-GL)** is a 1.3B parameters model which is a Continual pretraining from [FLOR-1.3B](https://huggingface.co/projecte-aina/FLOR-1.3B), which is based in [Bloom 1.7B](https://huggingface.co/bigscience/bloom-1b7).*
+
 👀 **Máis información sobre FLOR-1.3B-GL:** [tarxeta modelo oficial HF](https://huggingface.co/proxectonos/FLOR-1.3B-GL).
 
+*👀 **Learn more about FLOR-1.3B-GL:** [HF official model card](https://huggingface.co/proxectonos/FLOR-1.3B-GL).*
+
+
+🧠 **[Cerebras-1.3B-GL](https://huggingface.co/proxectonos/Cerebras-1.3B-GL)** é un modelo de parámetros 1.3B baseado en [Cerebras-GPT 1.3B](https://huggingface.co/cerebras/Cerebras-GPT-1.3B).
 
-🧠 **[Cerebras-1.3B-GL](https://huggingface.co/proxectonos/Cerebras-1.3B-GL)** é un modelo de parámetros 1.3B baseado en [Cerebras-GPT 1.3B](https:/ /huggingface.co/cerebras/Cerebras-GPT-1.3B).
+*🧠 **[Cerebras-1.3B-GL](https://huggingface.co/proxectonos/Cerebras-1.3B-GL)** is a 1.3B parameters model based in [Cerebras-GPT 1.3B](https://huggingface.co/cerebras/Cerebras-GPT-1.3B).*
 
 👀 **Máis información sobre Cerebras-1.3B-GL:** [tarxeta modelo oficial HF](https://huggingface.co/proxectonos/Cerebras-1.3B-GL)
+
+*👀 **Learn more about Cerebras-1.3B-GL:** [HF official model card](https://huggingface.co/proxectonos/Cerebras-1.3B-GL)*
 """
 
-markdown_description ={"en": markdown_description_en,"gl": markdown_description_gl}
 short_prompts_examples = [
     ["A receita tradicional das filloas é"], 
     ["O neno vivía preto de"]
@@ -60,10 +50,6 @@ generator_model_flor = pipeline("text-generation", model=model_id_flor)
 model_id_cerebras  = "proxectonos/Cerebras-1.3B-GL"
 generator_model_cerebras = pipeline("text-generation", model=model_id_cerebras, token=os.environ['TOKEN_HF'])
 
-# Load language texts ---------------------------------------------------------
-df_interface = pd.read_csv("interface_texts.csv")
-language = "gl"
-
 # Generation functions ---------------------------------------------------------
 def get_model(model_selection):
     if model_selection == "FLOR-1.3B-GL":
@@ -98,16 +84,6 @@ def predict(prompt, model_select, max_length, repetition_penalty, temperature):
     return generated_sequence
 
 # Gradio app ---------------------------------------------------------
-def get_text_lang(variable):
-    return df_interface.loc[df_interface['variable'] == variable, language].values[0]
-
-def change_language(demo):
-    if language == "gl":
-        language = "en"
-    else:
-        language = "gl"
-    demo.launch()
-
 def clear(): 
     return (
         None, 
@@ -140,62 +116,60 @@ def gradio_app():
     with gr.Blocks(theme=fronted_theme) as demo:
         with gr.Row():
             with gr.Column(scale=0.1):
-                change_lang = gr.Button(value=get_text_lang("change_lang"))
                 gr.HTML('<img src="https://huggingface.co/spaces/proxectonos/README/resolve/main/title-card.png" width="100%" style="border-radius: 0.75rem;">')
             with gr.Column():
-                gr.Markdown(markdown_description[language])
+                gr.Markdown(markdown_description)
         with gr.Row(equal_height=True):            
                 model_select = gr.Dropdown(
-                    label=get_text_lang("model_select"),
+                    label="Selecione un modelo / Select a model",
                     choices=MODEL_NAMES,
                     value=MODEL_NAMES[0],
                     interactive=True
                 )
         with gr.Row(equal_height=True):
             with gr.Column():
-                text_gl = gr.Textbox(label=get_text_lang("text_gl"), 
+                text_gl = gr.Textbox(label="Entrada / Input", 
                                      lines=6, placeholder="e.g. O neno vai a escola con ")
                 with gr.Row(variant="panel"):
-                        with gr.Accordion(get_text_lang("accordion_parameters"), open=False):
+                        with gr.Accordion("Parámetros do modelo / Model parameters", open=False):
                             max_length = Slider(
                                 minimum=1,
                                 maximum=200,
                                 step=1,
                                 value=30,
-                                label=get_text_lang("max_length")
+                                label="Max tokens"
                             )
                             repetition_penalty = Slider(
                                 minimum=0.1,
                                 maximum=4,
                                 step=0.1,
                                 value=1.3,
-                                label=get_text_lang("repetition_penalty")
+                                label="Penalización por repetición / Repetition penalty""
                             )
                             temperature = Slider(
                                 minimum=0,
                                 maximum=1,
                                 value=0.5,
-                                label=get_text_lang("temperature")
+                                label="Temperatura / Temperature"
                             )
-                generator_btn = gr.Button(value=get_text_lang("generator_btn"),variant='primary')
+                generator_btn = gr.Button(value="Xerar / Generate",variant='primary')
             with gr.Column():
-                generated_gl = gr.Textbox(label=get_text_lang("generated_gl_label"), 
+                generated_gl = gr.Textbox(label="Saída / Output", 
                                           lines=6, 
-                                          placeholder=get_text_lang("generated_gl_placeholder"),
+                                          placeholder="O texto xerado aparecerá aquí...",
                                           interactive=False,
                                           show_copy_button=True)
-                pass_btn = gr.Button(value=get_text_lang("pass_btn"))
-                clean_btn = gr.Button(value=get_text_lang("clean_btn"))
+                pass_btn = gr.Button(value="Pasar texto xerado á entrada / Pass generated text to input",variant='secondary')
+                clean_btn = gr.Button(value="Limpar / Clear",variant='secondary')
 
         generator_btn.click(predict, inputs=[text_gl, model_select, max_length, repetition_penalty, temperature], outputs=generated_gl, api_name="generate-flor-gl")
         clean_btn.click(fn=clear, inputs=[], outputs=[text_gl, generated_gl, max_length, repetition_penalty, temperature], queue=False, api_name=False)
         pass_btn.click(fn=pass_to_input, inputs=[generated_gl], outputs=[text_gl,generated_gl], queue=False, api_name=False)
-        change_lang.click(fn=change_language, inputs=[demo], outputs=[], queue=False, api_name=False)
-        
+         
         with gr.Row():
             with gr.Column(scale=0.5):
                 gr.Examples(
-                    label = get_text_lang("examples_short_prompts"),
+                    label = "Prompts curtos / Short prompts",
                     examples = short_prompts_examples,
                     inputs = [text_gl],
                     outputs = [max_length, repetition_penalty, temperature],
@@ -203,7 +177,7 @@ def gradio_app():
                     run_on_click = True
                 )
                 gr.Examples(
-                    label = get_text_lang("examples_few_shot"),
+                    label = "Prompts con poucos exemplos / Few-shot prompts",
                     examples = few_shot_prompts_examples,
                     inputs = [text_gl],
                     outputs = [max_length, repetition_penalty, temperature],

interface_texts.csv

@@ -1,5 +1,6 @@
 variable,en,gl
 change_lang, Cambiar a Galego, Switch to English
+change_lang_url,
 model_select,Model selection,Seleccione un modelo
 text_gl,Input,Entrada
 accordion_parameters,Model parameters,Parámetros do modelo