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| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline | |
| import torch | |
| model = AutoModelForSeq2SeqLM.from_pretrained("Mamadou2727/Feriji_model") | |
| tokenizer = AutoTokenizer.from_pretrained("facebook/m2m100_418M") | |
| device = "cuda:0" if torch.cuda.is_available() else "cpu" | |
| LANG_CODES = { | |
| "French": "fr", | |
| "Zarma": "yo" | |
| } | |
| def translate(text, candidates: int): | |
| """ | |
| Translate the text from French to Zarma | |
| """ | |
| src = LANG_CODES["French"] | |
| tgt = LANG_CODES["Zarma"] | |
| tokenizer.src_lang = src | |
| tokenizer.tgt_lang = tgt | |
| ins = tokenizer(text, return_tensors='pt').to(device) | |
| gen_args = { | |
| 'return_dict_in_generate': True, | |
| 'output_scores': True, | |
| 'output_hidden_states': True, | |
| 'length_penalty': 0.0, # don't encourage longer or shorter output, | |
| 'num_return_sequences': candidates, | |
| 'num_beams': candidates, | |
| 'forced_bos_token_id': tokenizer.lang_code_to_id[tgt] | |
| } | |
| outs = model.generate(**{**ins, **gen_args}) | |
| output = tokenizer.batch_decode(outs.sequences, skip_special_tokens=True) | |
| return '\n'.join(output) | |
| with gr.Blocks() as app: | |
| markdown = r""" | |
| # FERIJI Translator, The First French-Zarma Translator | |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/63cc1d4bf488db9bb3c6449e/AtOKLAaL5kt0VhRsxE0vf.png" width="500" height="300"> | |
| This 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**, was curated by **Elysabhete Ibrahim Amadou**, **Habibatou Abdoulaye Alfari**, **Adwoa Bremang**, **Dennis Owusu**, **Mamadou K. KEITA** and **Dr Christopher Homan**, with the aim to enhance linguistic studies for 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) | |
| with gr.Column(): | |
| input_text = gr.components.Textbox(lines=7, label="Français/French", value="") | |
| return_seqs = gr.Slider(label="Number of return sequences", value=1, minimum=1, maximum=12, step=1) | |
| outputs = gr.Textbox(lines=7, label="Zarma") | |
| translate_btn = gr.Button("Traduis!") | |
| translate_btn.click(translate, inputs=[input_text, return_seqs], outputs=outputs) | |
| app.launch(share=True) |