| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| tokenizer = AutoTokenizer.from_pretrained("rudrashah/RLM-hinglish-translator") | |
| model = AutoModelForCausalLM.from_pretrained("rudrashah/RLM-hinglish-translator") | |
| text = "mere paas 100 rupaye hain" | |
| template = "Hinglish:\n{hi_en}\n\nEnglish:\n{en}" | |
| input_text = tokenizer(template.format(hi_en=text,en=""),return_tensors="pt") | |
| output = model.generate(**input_text, max_length=250) | |
| english = tokenizer.decode(output[0]) | |
| english = english.replace("<bos>","").replace("<eos>","") | |
| english = english[len(template.format(hi_en=text,en="")):] | |
| print(english.strip()) |