YAML Metadata Warning: The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

English2Hinglish-Flan-T5-Base

This is a finetuned model of google/flan-t5-base with rvv-karma/English-Hinglish-TOP dataset.

Usage

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

model_name = "rvv-karma/English2Hinglish-Flan-T5-Base"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

input_text = "What are you doing?"
input_ids = tokenizer(input_text, return_tensors="pt")
output_ids = model.generate(**input_ids)
output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)

print(output_text)

Fine-tuning script

Google Colaboratory Notebook

References

DataCamp

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Dataset used to train rvv-karma/English2Hinglish-Flan-T5-Base