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597337dcb8
* added playground with 12 demos * change name to recipes, restyle navbar * add explanatory text to page * fix demo mapping * categorize demos, clean up design * styling * cateogry naming and emojis * refactor and add text demos * add view code button * remove opening slash in embed * styling * add image demos * adding plot demos * remove see code button * removed submodules * changes * add audio models * remove fun section * remove tests in image semgentation demo repo * requested changes * add outbreak_forecast * fix broken demos * remove images and models, add new demos * remove readmes, change to run.py, add description as comment * move to /demos folder, clean up dict * add upload_to_spaces script * fix script, clean repos, and add to docker file * fix python versioning issue * env variable * fix * env fixes * spaces instead of tabs * revert to original networking.py * fix rate limiting in asr and autocomplete * change name to demos * clean up navbar * move url and description, remove code comments * add tabs to demos * remove margins and footer from embedded demo * font consistency Co-authored-by: Abubakar Abid <abubakar@huggingface.co>
33 lines
1.3 KiB
Python
33 lines
1.3 KiB
Python
import gradio as gr
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
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import torch
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# this model was loaded from https://hf.co/models
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model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M")
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tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distilled-600M")
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device = 0 if torch.cuda.is_available() else -1
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LANGS = ["ace_Arab", "eng_Latn", "fra_Latn", "spa_Latn"]
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def translate(text, src_lang, tgt_lang):
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"""
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Translate the text from source lang to target lang
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"""
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translation_pipeline = pipeline("translation", model=model, tokenizer=tokenizer, src_lang=src_lang, tgt_lang=tgt_lang, max_length=400, device=device)
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result = translation_pipeline(text)
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return result[0]['translation_text']
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demo = gr.Interface(
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fn=translate,
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inputs=[
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gr.components.Textbox(label="Text"),
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gr.components.Dropdown(label="Source Language", choices=LANGS),
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gr.components.Dropdown(label="Target Language", choices=LANGS),
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],
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outputs=["text"],
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examples=[["Building a translation demo with Gradio is so easy!", "eng_Latn", "spa_Latn"]],
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cache_examples=False,
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title="Translation Demo",
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description="This demo is a simplified version of the original [NLLB-Translator](https://huggingface.co/spaces/Narrativaai/NLLB-Translator) space"
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)
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demo.launch() |