| import gradio |
| from transformers import GPT2LMHeadModel, GPT2Tokenizer, AdamW |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
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| model_name = "zaanind/gpt2_finetune_alpaca" |
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| tokenizer = GPT2Tokenizer.from_pretrained(model_name) |
| tokenizer.pad_token = tokenizer.eos_token |
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| model = GPT2LMHeadModel.from_pretrained(model_name) |
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| def translate(text): |
| prompt = f"<s>[INST] translate this sentence to sinhala - {text} [/INST] sure,here the translation of the provided text - " |
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| input_ids = tokenizer.encode(prompt, return_tensors='pt') |
| output = model.generate(input_ids, max_length=250, num_return_sequences=1) |
| translation = tokenizer.decode(output[0], skip_special_tokens=True) |
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| return translation |
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| def nmtapifunc(text): |
| text = translate(text) |
| return text |
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| gradio_interface = gradio.Interface( |
| fn=nmtapifunc, |
| inputs="text", |
| outputs="text", |
| title="ZoomAI Inference Server", |
| description="", |
| article="© Zaanind 2023-2024" |
| ) |
| gradio_interface.launch() |
