README.md

# Cheapity3 🐷
GPT3-like T5 model trained to generate text in multiple languages.

## Motivation
- GPT models are expensive run.
- GPT models are monolingual.

## Solution
- Maybe, Small Models aren't Terrible (*SMarT*) 
- Plus, they are cheaper to run.

I fine-tuned T5 on multiple languages (🇬🇧 English, 🇩🇪 German, 🇫🇷 French) and multiple academic text snippets from various 
domains like tech, law, finance and science etc. to generate text, just like GPT models do.

## Usage
- Provide some text e.g `"Italy, officially the Italian Republic is a country consisting of"`
- Tell Cheapity3 how many words you want to generate e.g `15` -- 😃 Yes, you can control the length.
- Cheapity3 reads your text and generates a continuation containing approximately 15 words.

```python
from transformers import AutoTokenizer, AutoModelWithLMHead

tokenizer = AutoTokenizer.from_pretrained("flexudy/cheapity3")

model = AutoModelWithLMHead.from_pretrained("flexudy/cheapity3")

input_text = "guess: Italy, officially the Italian Republic is a country consisting of { _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ }" # 15 words

inputs = tokenizer.encode(input_text, return_tensors="pt", truncation=True, max_length=512)

input_ids = inputs["input_ids"]

attention_mask = inputs["attention_mask"]

outputs = model.generate(
            input_ids=input_ids,
            attention_mask=attention_mask,
            max_length=128,
            do_sample=True,
            early_stopping=True,
            num_return_sequences=4,
            repetition_penalty=2.5
        )

for i in range(4):
    print(tokenizer.decode(outputs[i], skip_special_tokens=True, clean_up_tokenization_spaces=True))

# > 
# > 
# > 
# > 
```

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