Update app

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 import torch
 
+# Load the model and tokenizer
 model = AutoModelForSeq2SeqLM.from_pretrained("Mamadou2727/Feriji_model")
 tokenizer = AutoTokenizer.from_pretrained("facebook/m2m100_418M")
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
@@ -10,18 +11,21 @@ LANG_CODES = {
     "Zarma": "yo"
 }
 
-def translate(text, candidates: int):
+def translate(text, file, candidates: int):
     """
-    Translate the text from French to Zarma
+    Translate the text from French to Zarma. Can use text input or uploaded file.
     """
-
     src = LANG_CODES["French"]
     tgt = LANG_CODES["Zarma"]
-    
+
     # If a file is uploaded, use its content for translation
     if file is not None:
         text = file.read().decode("utf-8")
-        
+
+    # If there's no text input or file content, return an error message or empty string
+    if not text.strip():
+        return "No text provided for translation."
+
     tokenizer.src_lang = src
     tokenizer.tgt_lang = tgt
 
@@ -31,7 +35,7 @@ def translate(text, candidates: int):
         'return_dict_in_generate': True,
         'output_scores': True,
         'output_hidden_states': True,
-        'length_penalty': 0.0,  # don't encourage longer or shorter output,
+        'length_penalty': 0.0,
         'num_return_sequences': candidates,
         'num_beams': candidates,
         'forced_bos_token_id': tokenizer.lang_code_to_id[tgt]
@@ -43,43 +47,14 @@ def translate(text, candidates: int):
     return '\n'.join(output)
 
 with gr.Blocks() as app:
-    markdown = r"""
-        # Feriji-fr-to-dje v.1.1, Proudly made by Elysabhete, Habibatou & Mamadou K.
-        
-        <img src="https://cdn-uploads.huggingface.co/production/uploads/63cc1d4bf488db9bb3c6449e/AtOKLAaL5kt0VhRsxE0vf.png" width="500" height="300">
-        
-        Feriji-fr-to-dje is a beta version of the French to Zarma translator.
-            
-        ## Intended Uses & Limitations        
-        
-        This model is intended for academic research and practical applications in machine translation. It can be used to translate French text to Zarma and vice versa. Users should note that the model's performance may vary based on the complexity and context of the input text.
-            
-        ## Authors:
-        The project, **Feriji dataset and Feriji-fr-to-dje**, was curated by **Elysabhete Ibrahim Amadou** and **Mamadou K. KEITA**, with the aim to enhance linguistic studies and translation capabilities between French and Zarma.
-            
-        ## Citations
-            
-        If you use this dataset or model in your research, please cite it as follows:
-            
-        @dataset{Feriji,
-          author       = {Habibatou Abdoulaye Alfari, Elysabhete Ibrahim Amadou and Mamadou K. KEITA},
-          title        = {Feriji, a French-Zarma Parallel Corpus},
-          year         = 2023,
-          publisher    = {GitHub},
-          journal      = {GitHub repository},
-          howpublished = {\url{https://github.com/27-GROUP/Feriji}}
-        }
-    """
-
     with gr.Row():
-        gr.Markdown(markdown)
+        gr.Markdown("Your markdown content here")
         with gr.Column():
             input_text = gr.components.Textbox(lines=7, label="Input Text", value="")
             upload_file = gr.File(label="Upload File")
             return_seqs = gr.Slider(label="Number of return sequences", value=1, minimum=1, maximum=12, step=1)
             outputs = gr.Textbox(lines=7, label="Output Text")
-
             translate_btn = gr.Button("Traduis!")
             translate_btn.click(translate, inputs=[input_text, upload_file, return_seqs], outputs=outputs)
-            
+
 app.launch(share=True)