Translate-EN-to-TR

Name: Translate-EN-to-TR
Author: suayptalha

license:apache-2.0

suayptalha

Language Model

OTHER

100B params

New

14 downloads

Early-stage

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Edge AI:

Mobile

Laptop

Server

224GB+ RAM

Mobile

Laptop

Server

Quick Summary

This is a English to Turkish translator t5-base finetuned model on Helsinki-NLP/opus-100 License: This model is on Apache-2.

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

94GB+ RAM

Code Examples

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

python

#Load the model and tokenizer
plain_text = "Translate to Turkish: " #English text here!
inputs = tokenizer(cipher_text, return_tensors="pt", padding=True, truncation=True, max_length=256).to(device)
outputs = model.generate(inputs["input_ids"], max_length=256)
translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

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