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Update app.py
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app.py
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@@ -4,7 +4,10 @@ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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import torch
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title = """# ππ»Welcome To πTonic'sπAya-101"""
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description = """
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device = "cuda"
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checkpoint = "CohereForAI/aya-101"
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@@ -12,18 +15,10 @@ tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint, torch_dtype=torch.bfloat16, low_cpu_mem_usage=True, device_map=device)
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@spaces.GPU
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def aya(text):
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"""
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Translates the input text to English using the Aya model.
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Assumes the model can automatically detect the input language.
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"""
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model.to(device)
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inputs = tokenizer.encode(text, return_tensors="pt").to(device)
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outputs = model.generate(inputs, max_new_tokens=128)
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translation = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return translation
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@@ -31,11 +26,11 @@ def main():
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with gr.Blocks() as demo:
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gr.Markdown(title)
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gr.Markdown(description)
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output_text = gr.Textbox(label="πAya", interactive=False)
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input_text = gr.Textbox(label="π£οΈInput Text")
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submit_button = gr.Button("Translate") # Add a button to submit the input
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submit_button.click(fn=aya, inputs=input_text, outputs=output_text)
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demo.launch()
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import torch
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title = """# ππ»Welcome To πTonic'sπAya-101"""
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description = """The Aya model is a massively multilingual generative language model that follows instructions in 101 languages. You can build with this endpoint usingπAya-101 available here : [CohereForAI/aya-101](https://huggingface.co/CohereForAI/aya-101). Try your own language out !
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You can also use πAya-101 by cloning this space. Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/Aya?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> the easiest way to use Aya-101 is to use the Cohere CLI and their playground. Try finetuning the version with open weights !
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Join us : πTeamTonicπ is always making cool demos! Join our active builder's π οΈcommunity π» [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On π€Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) Math with [introspector](https://huggingface.co/introspector) On πGithub: [Tonic-AI](https://github.com/tonic-ai) & contribute toπ [MultiTonic](https://github.com/Tonic-AI/MultiToniic)π€Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant π€
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"""
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device = "cuda"
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checkpoint = "CohereForAI/aya-101"
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model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint, torch_dtype=torch.bfloat16, low_cpu_mem_usage=True, device_map=device)
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@spaces.GPU
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def aya(text, max_new_tokens):
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model.to(device)
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inputs = tokenizer.encode(text, return_tensors="pt").to(device)
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outputs = model.generate(inputs, max_new_tokens=max_new_tokens)
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translation = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return translation
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with gr.Blocks() as demo:
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gr.Markdown(title)
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gr.Markdown(description)
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input_text = gr.Textbox(label="π£οΈInput Text")
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max_new_tokens_slider = gr.Slider(minimum=150, maximum=1648, step=1, value=250, label="Size of your inputs and answer")
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submit_button = gr.Button("UseπAya")
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output_text = gr.Textbox(label="πAya", interactive=False)
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submit_button.click(fn=aya, inputs=[input_text, max_new_tokens_slider], outputs=output_text)
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demo.launch()
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